R 2.1.0 - en to zh translation catalogue (648 entries)

en: %d factors is too many for %d variables
zh: %2$d变量不能有%1$d这么多的因子

en: %d missing values deleted
zh: 删除了%d个遺漏值

en: %d responses, but only %d variables
zh: %d个反应, 但只有%d个变量

en: ' ignored
zh: ' 略过不用

en: '%s' cannot be of mode '%s'
zh: '%s'不可能有'%s'状态

en: 'ColSideColors' must be a character vector of length ncol(x)
zh: 'ColSideColors'必需是长度为ncol(x)的字节向量

en: 'FUN' must always return a scalar
zh: 'FUN'必需回覆纯量

en: 'P.values' is TRUE, but 'has.Pvalue' is not
zh: 'P.values'值是TRUE, 但'has.Pvalue'不是

en: 'RowSideColors' must be a character vector of length nrow(x)
zh: 'RowSideColors'必需是长度为nrow(x)的字节向量

en: 'V' is not a square numeric matrix
zh: 'V'不是正方形的数值矩阵

en: 'X' is not a dendrogram
zh: 'X'不是系統樹圖

en: 'X' matrix has %d responses, 'Y' has %d responses
zh: 'X'矩阵有%d个反应, 而'Y'有%d个

en: 'X' matrix was collinear
zh: 'X'是同線矩阵

en: 'acf' must be of length two or more
zh: 'acf'的长度必需是一或二

en: 'alpha', 'beta' and 'gamma' must be within the unit interval.
zh: 'alpha', 'beta'和'gamma'必需在单位区间内。

en: 'anova' is only defined for sequences of "nls" objects
zh: 'anova'只适用于"nls"目标对象序列

en: 'anova' object must have colnames
zh: 'anova'目标对象必需有列名

en: 'approx' requires n >= 1
zh: 'approx'需要n >= 1

en: 'ar' part of model is not stationary
zh: 模型的'ar'部分不平穩

en: 'bw' is not positive.
zh: 'bw'不是正数。

en: 'by' must be a list
zh: 'by' 必需是串列

en: 'centers' must be a number or a matrix
zh: 'centers'必需是个数字或矩阵

en: 'coef' does not have the correct length
zh: 'coef'的长度不对

en: 'coef' must be a vector
zh: 'coef'必需是向量

en: 'coef' must define a contrast, i.e., sum to 0
zh: 'coef'必需设定对比, 如, 总和为0

en: 'coef' must have same length as 'contrast.obj'
zh: 'coef'的长度必需同'contrast.obj'长度一样

en: 'col.vars' missing or incorrect
zh: 'col.vars'有遺漏或设定得不对

en: 'conf.level' must be a single number between 0 and 1
zh: 'conf.level'必需是一个数值在0到1之间的数字

en: 'covmat' is not a valid covariance list
zh: 'covmat'这个协方差串列有错

en: 'covmat' is of unknown type
zh: 'covmat'的种类不对

en: 'cterms' argument must match terms in model object
zh: 'cterms'变元必需同模型目标对象里的项相配

en: 'cutpoints' must be unique in 0 < cuts < 1, but are =
zh: 'cutpoints'必需在0 < cuts < 1之间，而相互必需不同, 但实际上是 =

en: 'cutpoints' must be unique, but are =
zh: 'cutpoints'相互必需不同，但实际上是 =

en: 'data' must be a data.frame, not a matrix or an array
zh: 'data'必需是数据框, 不能是矩阵或陣列

en: 'degree' must be 0, 1 or 2
zh: 'degree'必需是0, 1或2

en: 'degree' must be at least 1
zh: 'degree'至少为1

en: 'degree' must be less than number of points
zh: 'degree'小于数据点的数目

en: 'end' value not changed
zh: 'end'值没有变化

en: 'family' argument seems not to be a valid family object
zh: 'family'变元的值不是正确的分布族目标对象

en: 'family' not recognized
zh: 'family'设定得不对

en: 'file' must be a character string or connection
zh: 'file'必需是字符串或链结

en: 'filter' is longer than time series
zh: 'filter'的长度比时间序列的长度要长

en: 'formula' has '.' in both left and right hand side
zh: 'formula'的公式左右两边都有'.'

en: 'formula' missing
zh: 没有'formula'

en: 'formula' missing or incorrect
zh: 'formula'遺漏或有错

en: 'formula' missing or invalid
zh: 'formula'遺漏或有错

en: 'formula' must have both left and right hand sides
zh: 'formula'的公式左右两边都必需存在

en: 'frequency' and 'deltat' are both supplied and are inconsistent
zh: 'frequency'和'deltat'都被设定，但它们的值相互矛盾

en: 'id.n' must be in {1,..,%d}
zh: 'id.n'必需在{1,..,%d}中

en: 'init' is of the wrong length
zh: 'init'长度不对

en: 'init'; must have 1 or %d cols
zh: 'init'; 必需有1或%d个列

en: 'iter.max' must be positive
zh: 'iter.max'必需是正数

en: 'k' and 'h' must be a scalar
zh: 'k'和'h'必需都是纯量

en: 'k' is bigger than 'n'!  Changing 'k' to
zh: 'k'比'n'大! 把'k'改成

en: 'k' is not a kernel
zh: 'k'不是内核

en: 'k' is not an integer
zh: 'k'不是整数

en: 'k' must be in {1, 2, ..  n - 1}
zh: 'k'必需是{1, 2, ..  n - 1}中的一个

en: 'k' must be odd!  Changing 'k' to
zh: 'k'只能是奇数! 把'k'改成

en: 'k' must be positive
zh: 'k'必需是正数

en: 'k1' is not a kernel
zh: 'k1'不是内核

en: 'k2' is not a kernel
zh: 'k2'不是内核

en: 'kernapply' is not available for object 'x'
zh: 'kernapply'不适用于目标对象 'x'

en: 'lag.max' must be at least 1
zh: 'lag.max'至少必需为1

en: 'low' and 'high' cannot be both TRUE
zh: 'low'和'high'不能同时都为TRUE

en: 'm' is less than 1
zh: 'm'小于1

en: 'm' must be numeric with non-negative integers
zh: 'm'必需是非负的整数

en: 'main' must be TRUE, FALSE, NULL or character (vector).
zh: 'main'必需是TRUE, FALSE, NULL或字符(向量) 。

en: 'margins' must be a numeric vector of length 2
zh: 'margins'必需是长度为二的数值向量

en: 'merge' and 'height' do not fit!
zh: 'merge'和'height'不合!

en: 'merge' component in dendrogram must be integer
zh: 系統樹圖的'merge'组件必需是整数

en: 'mlm' objects with weights are not supported
zh: 目前不支持带重量的'mlm'目标对象

en: 'model$order' must be of length 3
zh: 'model$order'的长度必需为3

en: 'model' must be list
zh: 'model'必需是串列

en: 'model.tables' is not implemented for multiple responses
zh: 'model.tables'没有为多反应实现

en: 'mu' must be a single number
zh: 'mu'必需是单一数字

en: 'mult' must be integer >= 2, typically = 30
zh: 'mult'必需是 >= 2的正数，一般等于30

en: 'n' must be a positive integer >= 'x'
zh: 'n'必需是 >= 'x'的正整数

en: 'newdata' does not contain the variables needed
zh: 'newdata'不包含需要的变量

en: 'newdata' does not have named columns matching one or more of the original columns
zh: 'newdata'同原始数据没有相同的列名

en: 'newdata' does not have the correct number of columns
zh: 'newdata'列的数目不对

en: 'newdata' had %d rows but variable(s) found have %d rows
zh: 'newdata'有%d行但变量里有%d行

en: 'newdata' must be a matrix or data frame
zh: 'newdata'必需是矩阵或是数据框

en: 'nknots' must be numeric <= n
zh: 'nknots'必需是 <= n的数值

en: 'nterms' is missing with no default
zh: 没有'nterms'的值，也没有默認值

en: 'object' does not include an error 'qr' component
zh: 'object'不包含误差'qr'组件

en: 'object' has no 'effects' component
zh: 'object'没有'effects'组件

en: 'or' must be a single number between 0 and Inf
zh: 'or'必需是在0和Inf之间的一个数值

en: 'order' must be a non-negative numeric vector of length 3
zh: 'order'必需是长度为三的非负数值向量

en: 'order.dendrogram' requires a dendrogram
zh: 'order.dendrogram'必需用在系統樹圖上

en: 'order.max' must be >= 0
zh: 'order.max'必需 >= 0

en: 'order.max' must be >= 1
zh: 'order.max'必需 >= 1

en: 'p' must be a single number between 0 and 1
zh: 'p'必需是在0到1之间的数值

en: 'p' must be between 0 and 0.5
zh: 'p'必需在0和0.5之间

en: 'p' must have the same length as 'x' and 'n'
zh: 'p'的长度必需同'x'和'n'的相等

en: 'params' has wrong length
zh: 'params'的长度不对

en: 'plot.stepfun' called with wrong type of argument 'x'
zh: 調用'plot.stepfun'时变元'x'的种类不对

en: 'ppr' applies only to numerical variables
zh: 'ppr'只适用于数值变量

en: 'princomp' can only be used with more units than variables
zh: 'princomp'只能在单位比变量多的情况下使用

en: 'print.level' must be in {0,1,2}
zh: 'print.level'必需是{0,1,2}

en: 'prob' and 'mu' both specified
zh: 'prob'和'mu'不能同时设定

en: 'probs' outside [0,1]
zh: 'probs'在[0,1] 外

en: 'proj' is not implemented for "mlm" fits
zh: 'proj'还没有为"mlm"拟合实现

en: 'proj' is not implemented for multiple responses
zh: 'proj'还没有为多反应实现

en: 'r' is less than 0
zh: 'r'小于0

en: 'r' is less than 1
zh: 'r'小于1

en: 'ratio' must be a single positive number
zh: 'ratio'必需是单一的正数

en: 'ref' must be an existing level
zh: 'ref'必需是存在的层次

en: 'relevel' only for factors
zh: 'relevel'只适用于因子

en: 'row.var.names' missing
zh: 'row.var.names'有遺漏

en: 'scale' is outside [0, 1]
zh: 'scale'在[0, 1] 值域外

en: 'scores' argument is of the wrong length
zh: 'scores'变元长度对对

en: 'scores' must all be different numbers
zh: 'scores'内包含的数值不能都是相同的

en: 'se.fit' not yet implemented for multivariate models
zh: 'se.fit'没有为多变量的模型实现

en: 'seasonal$order' must be a non-negative numeric vector of length 3
zh: 'seasonal$order'必需是长度为三的非负数值向量

en: 'seasonal' must be a list with component 'order'
zh: 'seasonal'必需是带'order'组件的串列

en: 'sig.level' must be numeric in [0, 1]
zh: 'sig.level'必需是在[0, 1] 里的数值

en: 'span' must be between 0 and 1.
zh: 'span'必需在0和1之间。

en: 'start' and 'table' must be same length
zh: 'start'和'table'的长度必需相等

en: 'start' cannot be after 'end'
zh: 'start'不能大于'end'

en: 'start' must have %d rows
zh: 'start'必需有%d行

en: 'start' value not changed
zh: 'start'值没有变化

en: 'times' is wrong length
zh: 'times'的长度不对

en: 'ts' object must have one or more observations
zh: 'ts'目标对象至少必需有一个或多个观察量

en: 'variance' "%s" is invalid: possible values are "mu(1-mu)", "mu", "mu^2", "mu^3" and "constant"
zh: 'variance' "%s"不对：只能用"mu(1-mu)", "mu", "mu^2", "mu^3"和"constant"其中之一

en: 'varying' arguments must be the same length
zh: 'varying'变元的长度必需相同

en: 'varying' has wrong length
zh: 'varying'长度不对

en: 'varying' must be in 1:length(pars)
zh: 'varying'必需在1:length(pars) 之间

en: 'varying' must be logical, integer or character
zh: 'varying'必需是逻辑值，整数值或字符

en: 'vec' contains NAs
zh: 'vec'含NA

en: 'vec' must be sorted non-decreasingly
zh: 'vec'必需由小到大排序

en: 'weights' must all be finite
zh: 'weights'的值必需都是有限的

en: 'weights' must not be negative
zh: 'weights'不能是负数的

en: 'which' must be in 1:6
zh: 'which'必需在1:6之间

en: 'which' specified no factors
zh: 'which'没有指定因子

en: 'which' specified some non-factors which will be dropped
zh: 'which'内的非因子略过不用

en: 'x' and 'g' must have the same length
zh: 'x'和'g'的长度必需相同

en: 'x' and 'n' must have the same length
zh: 'x'和'n'的长度必需相等

en: 'x' and 'p' must have the same number of elements
zh: 'x'和'p'必需包含同样数目的单元

en: 'x' and 'w' must have the same length
zh: 'x'和'w'的长度必需相同

en: 'x' and 'weights' have unequal length
zh: 'x'和'weights'的长度必需相同

en: 'x' and 'y' must have at least 2 levels
zh: 'x'和'y'至少有两个层次

en: 'x' and 'y' must have the same length
zh: 'x'和'y'的长度必需相同

en: 'x' and 'y' must have the same number of levels (minimum 2)
zh: 'x'和'y'必需有相同数目的层次(最少要有两层)

en: 'x' contains missing values
zh: 'x'内含遺漏值

en: 'x' has been rounded to integer:
zh: 'x'捨入成正数:

en: 'x' has entries too large to be integer
zh: 'x'的正数值太大

en: 'x' has rank 0
zh: 'x'的秩为0

en: 'x' is empty
zh: 'x'是空的

en: 'x' is not a vector
zh: 'x'不是向量

en: 'x' is not a vector or matrix
zh: 'x'不是向量或矩阵

en: 'x' is shorter than kernel 'k'
zh: 'x'比内核'k'要短

en: 'x' must at least have 2 elements
zh: 'x'至少有两个单元

en: 'x' must be a 3-dimensional array
zh: 'x'必需是3维陣列

en: 'x' must be a list with at least 2 elements
zh: 'x'必需是至少有两个单元的串列

en: 'x' must be a matrix
zh: 'x'必需是矩阵

en: 'x' must be a matrix or a data frame
zh: 'x'必需是矩阵或是数据框

en: 'x' must be a numeric matrix
zh: 'x'必需为数值矩阵

en: 'x' must be a time series or an ar() fit
zh: 'x'必需是时间序列或ar()拟合

en: 'x' must be an "ftable" object
zh: 'x'必需是"ftable"目标对象

en: 'x' must be between %s and %s
zh: 'x'必需在%s和%s之间

en: 'x' must be between -1 and 1
zh: 'x'必需在-1和1之间

en: 'x' must be between 0 and 1 for periodic smooth
zh: 做周期平滑时'x'必需在0和1之间

en: 'x' must be coefficient matrix/data frame
zh: 'x'必需是係數矩阵/数据框

en: 'x' must be non-negative
zh: 'x'必需为非负数

en: 'x' must be nonnegative and integer
zh: 'x'必需是非负的整数

en: 'x' must be numeric
zh: 'x'必需为数值

en: 'x' must be numeric or logical
zh: 'x'必需是数值或逻辑值

en: 'x' must be square with at least two rows and columns
zh: 'x'必需是正方形的至少有两列和两行的矩阵

en: 'x' must contain finite values only
zh: 'x'只能包含有限值

en: 'x' must have 1 or more non-missing values
zh: 'x'必需含一或多个非遺漏值

en: 'x' must have 2 columns
zh: 'x'必需有两列

en: 'x' must have at least 2 rows and 2 columns
zh: 'x'至少有两行和两列

en: 'x' must have at least 2 rows and columns
zh: 'x'至少必需有两行和两列

en: 'x' must have length >= 1
zh: 'x'的长度必需 >= 1

en: 'x', 'y', and 'z' must have the same length
zh: 'x', 'y',和'z'的长度必需相等

en: 'xi' has not the right length
zh: 'xi'的长度不对

en: 'xreg' and 'newxreg' have different numbers of columns
zh: 'xreg'和'newxreg'有不同数目的列

en: 'xreg' is collinear
zh: 'xreg'是同線的

en: 'xy.labels' must be logical or character
zh: 'xy.labels'必需是逻辑值或是字符

en: 'y' has rank 0
zh: 'y'的秩为0

en: 'y' is missing for paired test
zh: 配对检验时没有设定'y'

en: 'y' must be numeric
zh: 'y'必需是数值

en: 'y' must be numeric or a string naming a valid function
zh: 'y'必需是数值，否则的话请用字符串指名正确的函数

en: 'y' must be numeric vector
zh: 'y'必需是数值向量

en: 'y' must be one longer than 'x'
zh: 'y'必需比'x'长

en: 'y', 'groups' and 'blocks' must have the same length
zh: 'y', 'groups'和'blocks'的长度必需相同

en: 0 (non-NA) cases
zh: 没有(非NA)案例可用

en: 0s in V(mu)
zh: V(mu) 里有0

en: AIC is not defined for this model, so 'step' cannot proceed
zh: 这个模型没有AIC定义，因此不能用'step'这一功能

en: Burg's algorithm only implemented for univariate series
zh: Burg的算法只为单变量序列实现

en: Cannot compute exact p-value with ties
zh: 无法给连结計算精確的p值

en: Cannot compute exact p-values with ties
zh: 无法给连结計算精確的p值

en: Chi-squared approximation may be incorrect
zh: Chi-squared近似算法有可能不准

en: Colv = "Rowv" but nrow(x) != ncol(x)
zh: Colv = "Rowv" 但 nrow(x) != ncol(x)

en: Consider providing an as.hclust.%s() method
zh: 请考虑提供as.hclust.%s()这一方法

en: Convergence failure:
zh: 没有收斂：

en: Design is unbalanced - use se.contrast() for se's
zh: 设计不平衡 - 用se.contrast()算标准误

en: Error() model is singular
zh: Error()模型奇异

en: F test assumes quasi%s family
zh: F检验假設quasi%s家族

en: Frequency not changed
zh: 頻率没有变化

en: Logical `hessian' argument not allowed.  See documentation.
zh: 不能有逻辑值的`hessian变元。请参考说明书。'

en: MA part of model is not invertible
zh: 模型的MA部分非可逆

en: MLE only implemented for univariate series
zh: MLE只为单变量序列实现

en: NA lev[]; probably smoothing parameter 'spar' way too large!
zh: NA lev[];很可能平滑参数'spar'的值太大了!

en: NA values not allowed in 'd'
zh: 'd'里不允许有NA值

en: NA's are not allowed in 'groups' or 'blocks'
zh: 'groups'或'blocks'里不能有NA

en: NA's are not allowed in groups or blocks
zh: 分组或区组里不能有NA

en: NAs are not allowed
zh: 不能有NA

en: NAs in 'x'
zh: 'x'里不能有NA

en: NAs in V(mu)
zh: V(mu) 里有NA

en: NAs in d(mu)/d(eta)
zh: d(mu)/d(eta) 里有NA

en: NAs present: setting 'delta' to -1
zh: 有NA：把'delta'设成-1

en: PCA applies only to numerical variables
zh: PCA只适用于数值变量

en: Requested conf.level not achievable
zh: 无法达到所要求的conf.level

en: SEs for type '%s' are not yet implemented
zh: 还没有为'%s'种类实现标准误的算法

en: Standard error information not returned as design is unbalanced. 
    Standard errors can be obtained through 'se.contrast'.
zh: 因为设计是不平衡的，没有回覆标准误信息。
    但可以通过'se.contrast'来计算标准误。

en: Upper or lower bounds ignored unless algorithm = "port"
zh: 除非algorithm = "port"，上限或下限将略过不用

en: X does not define a subspace of M
zh: X不设定M的子空间

en: X matrix has rank %d, but only %d observations
zh: X矩阵的秩为%d, 但只有%d个观察量

en: _NOT_ converged in
zh: 没有聚合于

en: a limit is missing
zh: 極限有遺漏

en: algorithm did not converge
zh: 算法没有聚合

en: algorithm stopped at boundary value
zh: 算法在边界值停止

en: all 'x' values are identical
zh: 所有'x'的值都是一样的

en: all 'x' values must be non-negative to fit the Weibull growth model
zh: 所有'x'的值都必需是非负的才能拟合Weibull成长模型

en: all elements of 'which' must be between 1 and %d
zh: 'which'的所有单元值都必需在1和%d之间

en: all entries of 'x' must be nonnegative and finite
zh: 'x'的所有值都必需是非负的有限值

en: all group levels must be finite
zh: 所有组的层次都必需是有限的

en: all groups must contain data
zh: 所有的组都必需包含数据

en: all observations are in the same group
zh: 所有的观察量都属于同一个组

en: all parameters were fixed
zh: 所有参数值都是固定的

en: all times contain an NA
zh: 所有的时间都包含NA

en: all weights should be non-negative
zh: 所有的重量都必需是非负值

en: alternative must be "two.sided", "less" or "greater"
zh: 必需在"two.sided", "less"或"greater"中选一个

en: ambiguous clustering method
zh: 群集方法不明确

en: ambiguous distance method
zh: 距离方法不明确

en: anova is only defined for sequences of "nls" objects
zh: anova只适用于"nls"目标对象序列

en: are just disregarded.
zh: 略过不用。

en: argument 'object' has an impossible length
zh: 变元'object'的长度不可能取这个值

en: argument 'sides' must be 1 or 2
zh: 变元'sides'必需是1或2

en: argument 'x' cannot be coerced to class "hclust"
zh: 无法将'x'变元強制转换成"hclust"类别

en: argument 'x' must be numeric
zh: 变元'x'必需是数值

en: argument does not include a 'qr' component
zh: 变元不包含'qr'组件

en: argument does not include an 'effects' component
zh: 变元不包含'effects'组件

en: arguments must have the same length
zh: 变元的长度必需一样

en: at least one entry of 'x' must be positive
zh: 'x'里至少要包含一个正值

en: attempt to smooth NA values
zh: 不能平滑NA值

en: attempt to smooth non-numeric values
zh: 不能平滑非数值数据

en: bad value for 'end'
zh: 'end'值不对

en: bad value for 'lag' or 'differences'
zh: 'lag'或'differences'的值有错

en: bad value for 'start'
zh: 'start'的值不对

en: bandwidth 'k' must be >= 1 and odd!
zh: 頻寬'k'必需 >= 1而且还是奇数!

en: baseline group number out of range
zh: 基線组在值域外

en: biplots are not defined for complex PCA
zh: 复数的PCA画不出biplot

en: both 'span' and 'enp.target' specified: 'span' will be used
zh: 'span'和'enp.target'同时有设定：只用'span'的值

en: both 'x' and 'covmat' were supplied: 'x' will be ignored
zh: 同时提供了'x'和'covmat': 'x'略过不用

en: bounds can only be used with method L-BFGS-B
zh: 只有在用L-BFGS-B方法时才能定优化界限

en: burn-in 'n.start' must be as long as 'ar + ma'
zh: 算法老化时'n.start'必需同'ar + ma'的大小一样

en: can use ci.type="ma" only if first lag is 0
zh: 只有在第一个滯後为0时才能用ci.type="ma"

en: cannot calculate REML log-likelihood for "nls" objects
zh: 无法为"nls"目标对象计算REML log-likelihood

en: cannot change frequency from %g to %g
zh: 无法将頻率从%g改到%g

en: cannot compute asymptotic confidence set or estimator
zh: 无法計算渐近置信集或估计量

en: cannot compute confidence set, returning NA
zh: 无法計算置信集, 回覆NA

en: cannot compute correct p-values with ties
zh: 在有连结的情况下无法正确計算p-值

en: cannot compute estimate, returning NA
zh: 无法計算估计量, 回覆NA

en: cannot compute exact confidence interval with ties
zh: 有连结时无法計算精確的置信区间

en: cannot compute exact confidence interval with zeroes
zh: 有0时无法計算精確的置信区间

en: cannot compute exact confidence intervals with ties
zh: 无法精確計算有连结的置信区间

en: cannot compute exact p-value with ties
zh: 无法精確計算有连结的p-值

en: cannot compute exact p-value with zeroes
zh: 有0时无法計算精確的p值

en: cannot compute simulated p-value with zero marginals
zh: 无法用0邊緣計算模拟p-值

en: cannot find valid starting values: please specify some
zh: 找不到有效的初始值: 请设定

en: cannot fit an asymptotic regression model to these data
zh: 无法用这些数据来拟合渐近迴歸模型

en: cannot fit models without level ('alpha' must not be 0).
zh: 无法拟合没有层次的模型('alpha'不能为0) 。

en: cannot handle 'pairwise.complete.obs'
zh: 不知如何處理'pairwise.complete.obs'

en: cannot plot more than 10 series as "multiple"
zh: 无法将多于10个序列画成"multiple"

en: cannot recognize parameter name
zh: 没有这样的参数名

en: cannot use dots in formula with given data
zh: 按照所提供的数据无法在公式里用点符号

en: cannot use more inner knots than unique 'x' values
zh: 内部结点数止比相互不同的'x'数目要多

en: coefficients do not add to 1
zh: 係數总和不是1

en: collapsing to unique 'x' values
zh: 折拢'x'成相互不同的值

en: column dendrogram ordering gave index of wrong length
zh: 行系統樹圖排序索引结果的长度出了错

en: columns of 'contrast.obj' must define a contrast (sum to zero)
zh: 'contrast.obj'的列必需设定成对比(总和为0)

en: columns of 'contrast.obj' must define a contrast(sum to zero)
zh: 'contrast.obj'的列必需设定对比(总和为0)

en: contrasts apply only to factors
zh: 对比只适用于因子

en: contrasts can be applied only to factors with 2 or more levels
zh: 对比只适用于有两个或多于两个层次的因子

en: contrasts not defined for %d degrees of freedom
zh: 对比不适用于%d自由度

en: contrasts not defined for 0 degrees of freedom
zh: 0自由度不能设对比

en: control argument must be a named list
zh: 控制变元必需是串列

en: converting non-invertible initial MA values
zh: 转换非可逆的MA初始值

en: covariance matrix is not non-negative definite
zh: 协方差矩阵不是非负定矩阵

en: coverage probability out of range [0,1)
zh: 覆蓋機率在值域 0,1) 外

en: crossvalidation with non-unique 'x' values seems doubtful
zh: 用有重复的'x'来做crossvalidation好象不太对

en: data are essentially constant
zh: 数据是恆量

en: data must be strictly non-negative for multiplicative Holt-Winters
zh: 乘法Holt-Winters所用的数据不能有负值

en: dendrogram node with non-positive #{branches}
zh: 系統樹圖節點有非正#{分支}

en: dendrogram non-leaf node with non-positive #{branches}
zh: 系統樹圖里有非正#{分支}的非叶節點

en: diagonal has non-finite entries
zh: 矩阵对角含无限值

en: did not converge in
zh: 没有聚合于

en: did not converge in %d iterations
zh: %d迭代没有聚合

en: dimension 0 in 'x' or 'y'
zh: 'x'或'y'的维度为0

en: distances must be result of 'dist' or a square matrix
zh: 距离必需是'dist'计算的结果或是正方形矩阵

en: each dimension in table must be >= 2
zh: 表的每个维度都必需 >= 2

en: each element of '%s' must be logical
zh: '%s'的所有单元都必需是逻辑值

en: eff.aovlist: non-orthogonal contrasts would give an incorrect answer
zh: eff.aovlist: 用非正交对比来算的结果会出错

en: either 'k' or 'h' must be specified
zh: 'k'和'h'中必需设定一个

en: elements of 'k' must be between 1 and %d
zh: 'k'的单元必需在1和%d之间

en: elements of 'n' must be positive
zh: 'n'的单元必需都是正的

en: elements of 'p' must be in (0,1)
zh: 'p'的单元必需在(0,1) 里

en: elements of 'x' must be nonnegative
zh: 'x'的单元必需都是非负的

en: elements of 'x' must not be greater than those of 'n'
zh: 'x'的单元不能比'n'的单元大

en: empty cluster: try a better set of initial centers
zh: 空的群集: 请试试更精确一点的初始中心集

en: empty model supplied
zh: 提供的模型是空的

en: exactly one of 'groups', 'n', 'between.var', 'within.var', 'power', and 'sig.level' must be NULL
zh: 'groups', 'n', 'between.var', 'within.var', 'power',和'sig.level'之中只能有一个取NULL值

en: exactly one of 'n', 'delta', 'sd', 'power', and 'sig.level' must be NULL
zh: 'n', 'delta', 'sd', 'power',和'sig.level'之中只能有一个取NULL值

en: exactly one of 'n', 'p1', 'p2', 'power', and 'sig.level' must be NULL
zh: 'n', 'p1', 'p2', 'power',和'sig.level'之中只能有一个取NULL值

en: extending time series when replacing values
zh: 替換时将时间序列延长

en: extra arguments
zh: 额外变元

en: extra arguments discarded
zh: 额外变元不用

en: f() values at end points not of opposite sign
zh: 位于极点边的f()值之正负号不相反

en: factor '%s' has new level(s) %s
zh: 因子'%s'有新的层次%s

en: factor analysis applies only to numerical variables
zh: 因子分析只适用于数值变量

en: factor analysis requires at least three variables
zh: 因子分析至少需要三个变量

en: first argument must be a "loess" object
zh: 第一个变元必需为"loess"目标对象

en: fitted probabilities numerically 0 or 1 occurred
zh: 拟合機率算出来是数值0或1

en: fitted rates numerically 0 occurred
zh: 拟合速率算出来是数值0

en: for the binomial family, y must be a vector of 0 and 1's
zh: binomial分布族中的y必需是由0和1组成的向量

en: for the quasibinomial family, y must be a vector of 0 and 1's
zh: quasibinomial分布族中的y必需由0和1组成的向量

en: formula '%s' must be of the form '~expr'
zh: 公式'%s'的形式必需是'~expr'

en: formula missing
zh: 没有公式

en: frequency must be a positive integer for BSM
zh: 用BSM时頻率必需正整数

en: grouping factor must have exactly 2 levels
zh: 分组因子只能有两层

en: if 'x' is not a matrix, 'y' must be given
zh: 如果'x'不是矩阵的话, 一定得有'y'值

en: if 'x' is not an array, 'y' must be given
zh: 如果'x'不是陣列的话, 必需提供'y'值

en: if 'x' is not an array, 'z' must be given
zh: 如果'x'不是陣列的话, 必需提供'z'值

en: ifault=%d. This should not happen
zh: ifault=%d。这不应该发生

en: incompatible dimensions
zh: 维度不相配

en: inconsistent specification of 'ar' order
zh: 'ar'度数设定有矛盾

en: inconsistent specification of 'ma' order
zh: 'ma'度数设定有矛盾

en: incorrect dimensions for 'xi'
zh: 'xi'的尺寸不对

en: incorrect length of 'x'
zh: 'x'长度不对

en: incorrect specification for 'col.vars'
zh: 'col.vars'设定不对

en: incorrect specification for 'formula'
zh: 'formula'设定不对

en: incorrect specification for 'row.vars'
zh: 'row.vars'设定不对

en: incorrect specification of 'table' or 'start'
zh: 当'table'或'start'正确地被设定时

en: incorrect variable names in lhs of formula
zh: 公式左边变量名字不对

en: incorrect variable names in rhs of formula
zh: 公式右边变量名字不对

en: initial centers are not distinct
zh: 初始中心的值有些是相同的

en: initial value not feasible
zh: 初始值不可用

en: inner loop 1; cannot correct step size
zh: 内循環1; 无法校正步驟大小

en: inner loop 2; cannot correct step size
zh: 内循環2; 无法校正步驟大小

en: insufficient observations
zh: 观察量数目不够

en: interactions are not allowed
zh: 不允许有交互作用项

en: internal error
zh: 内部错误

en: invalid 'abbr.colnames'
zh: 'abbr.colnames'不对

en: invalid 'contrasts.arg' argument
zh: 'contrasts.arg'变元不对

en: invalid 'control.spar'
zh: 'control.spar'不对

en: invalid 'data' argument
zh: 'data'变元不对

en: invalid 'lm' object:  no 'terms' nor 'qr' component
zh: 'lm'目标对象不对: 不包含'terms'或'qr'组件

en: invalid 'method':
zh: 'method'有错:

en: invalid 'tree' (merge component)
zh: 'tree'不对(将组件合并)

en: invalid 'x'
zh: 'x'不对

en: invalid 'y'
zh: 'y'不对

en: invalid (length 0) node in dendrogram
zh: 系統樹圖里的节点不对(长度为0)

en: invalid argument 'omit'
zh: 变元'omit'不对

en: invalid argument to 'getProfile'
zh: 'getProfile'变元不对

en: invalid clustering method
zh: 群集方法不对

en: invalid dendrogram
zh: 系統樹圖不对

en: invalid dissimilarities
zh: dissimilarities不对

en: invalid distance method
zh: 距离方法不对

en: invalid fitted means in empty model
zh: 空模型的拟合平均值不对

en: invalid formula
zh: 公式不对

en: invalid formula in deriv
zh: deriv里的公式不对

en: invalid interpolation method
zh: 内插方法不对

en: invalid length of members
zh: 成员长度不对

en: invalid linear predictor values in empty model
zh: 空模型里的线形従属変数值不对

en: invalid parameter values
zh: 参数值不对

en: invalid response type
zh: 反应种类不对

en: iterations
zh: 迭代

en: k must be between 2 and %d
zh: k必需在2和%d之间

en: length mismatch in convolution
zh: 卷积中的长度不相符

en: length of 'center' must equal the number of columns in 'x'
zh: 'center'的长度必需同'x'的列数相同

en: length of 'init' must equal length of 'filter'
zh: 'init'的长度必需等于'filter'的长度

en: length of 'p' must be 1 or equal the number of columns of 'x'
zh: 'p'的长度必需是1或等于'x'的列数

en: length of 'start' should equal %d and correspond to initial coefs for %s
zh: 'start'的长度应该是%d，同%s的初始系数相一致

en: length of 'wt' must equal the number of rows in 'x'
zh: 'wt'的长度必需同'x'的行数相同

en: length of FUN, %d,
     does not match the length of the margins, %d
zh: FUN的长度, %d,
    与边缘的长度, %d不相符

en: length of choices must be 2
zh: 选择长度必需为二

en: lengths of 'x' and 'w' must match
zh: 'x'和'w'的长度必需相等

en: lengths of 'x' and 'xreg' do not match
zh: 'x'和'xreg'的长度不一样

en: levels truncated to positive values only
zh: 层次被縮短成正值

en: link "%s" not available for binomial family, available links are "logit", ""probit", "cloglog", "cauchit" and "log"
zh: binomial分布族里没有"%s"这一鏈結函数；可以用的鏈結是"logit", ""probit", "cloglog", "cauchit"和"log"

en: link "%s" not available for gamma family, available links are "inverse", ""log" and "identity"
zh: gamma分布族里没有"%s"这一鏈結函数；可以用的鏈結是"inverse", ""log"和"identity"

en: link "%s" not available for gaussian family, available links are "inverse", "log" and "identity"
zh: gaussian分布族里没有"%s"这一鏈結函数；可以用的鏈結是"inverse", "log"和"identity"

en: link "%s" not available for inverse gauss family, available links are "inverse", "1/mu^2", "log" and "identity"
zh: 逆gauss分布族里没有"%s"这一鏈結函数；可以用的鏈結是"inverse", "1/mu^2", "log"和"identity"

en: link "%s" not available for poisson family; available links are "identity", "log" and "sqrt"
zh: poisson分布族里没有"%s"这一鏈結函数；可以用的鏈結是"identity", "log"和"sqrt"

en: link "%s" not available for quasipoisson family; available links are "identity", "log" and "sqrt"
zh: quasipoisson分布族里没有"%s"这一鏈結函数；可以用的鏈結是"identity", "log"和"sqrt"

en: link not available for quasibinomial family, available links are "logit", ", ""probit" and "cloglog"
zh: quasibinomial分布族里没有"%s"这一鏈結函数；可以用的鏈結是"logit", ", ""probit"和"cloglog"

en: link not recognised
zh: 没有这样的鏈結

en: lower < upper  is not fulfilled
zh: 没有满足lower < upper这个条件

en: lower scope is not included in model
zh: 模型里没有下範疇

en: maximum number of iterations must be > 0
zh: 迭代的最高值数目必需 > 0

en: medpolish() did not converge in %d iterations
zh: medpolish()经过%d个迭代仍没有聚合

en: method = '%s' is not supported. Using 'qr'
zh: 不支持method = '%s'。用'qr'

en: method L-BFGS-B uses 'factr' (and 'pgtol') instead of 'reltol' and 'abstol'
zh: L-BFGS-B方法用'factr'(和'pgtol') ，而不是'reltol'和'abstol'

en: midcache() of non-binary dendrograms only partly implemented
zh: 非二分系統樹圖的midcache()只实现了一部分

en: minimum occurred at one end of the range
zh: 最小值存在于值域的边界上

en: mismatched 'x' and 'y'
zh: 'x'和'y'不相配

en: missing observations deleted
zh: 删除了遺漏观察量

en: missing or negative weights not allowed
zh: 重量不允许是遺漏值或负值

en: missing values and NaN's not allowed if 'na.rm' is FALSE
zh: 'na.rm'如果设为FALSE的话不允许有遺漏值和NaN

en: missing values are not allowed in 'poly'
zh: 'poly'里不能有遺漏值

en: missing values in 'filter'
zh: 'filter'里有遺漏值

en: missing values in object
zh: 目标对象里有遺漏值

en: model 1
zh: 模型1

en: model frame and formula mismatch in model.matrix()
zh: model.matrix()里的模型框和公式不相配

en: model order:
zh: 模型顺序:

en: models were not all fitted to the same size of dataset
zh: 模型拟合时没有用同样大小的数据集

en: models with response
zh: 模型带反应

en: more cluster centers than data points
zh: 群集中心的数目要比数据点数目多

en: more cluster centers than distinct data points.
zh: 群集中心的数目要比数据点数目多。

en: must be 0 or 1
zh: 必需是0或1

en: must have 2 'symbols' for logical 'x' argument
zh: 逻辑'x'变元必需有两个'symbols'

en: must have at least 4 observations to fit an 'SSfol' model
zh: 至少有4个观察量才能拟合'SSfol'模型

en: must have length of response = length of second argument to 'SSfol'
zh: 反应的长度必需同'SSfol'的第二个变元的长度相同

en: must have n >= 2 objects to cluster
zh: 用群集时必需有n >= 2的目标对象

en: must have same number of columns in 'x' and 'centers'
zh: 'x'和'centers'的列数必需相等

en: must specify 'spans' or a valid kernel
zh: 必需设定'spans'或正确的内核

en: must supply either 'formula' or 'data'
zh: 至少要提供'formula'和'data'中间的一个

en: must supply one or more vectors
zh: 至少要提供一或多个向量

en: na.action must be a function
zh: na.action必需为函数

en: need an object with call component
zh: 需要一个有調用组件的目标对象

en: need at least 2 data points
zh: 至少需要两个数据点

en: need at least 2 points to select a bandwidth automatically
zh: 自动选择頻寬至少需要两个数据点

en: need at least 3 periods to compute seasonal start values
zh: 计算季節性初始值至少需要三个周期的数据

en: need at least four unique 'x' values
zh: 至少需要四个相互不同的'x'值

en: need at least two non-NA values to interpolate
zh: 调用内插至少需要两个非NA值的数据

en: need dendrograms where all leaves have labels
zh: 需要所有叶子都有标记的系統樹圖

en: need multiple response
zh: 需要多个反应

en: need numeric data
zh: 需要数值数据

en: need result of smooth.spline(*, keep.data=TRUE)
zh: 需要的是.spline(*, keep.data=TRUE) 的运算结果

en: negative values not allowed for the Poisson family
zh: Poisson分布族不能用负数

en: negative values not allowed for the quasiPoisson family
zh: quasiPoisson分布族不能用负数

en: negative weights not allowed
zh: 不能有负重量

en: neither 'x' nor 'covmat' supplied
zh: 'x'和'covmat'都没有被设定

en: no 'add1' method implemented for "mlm" models
zh: "mlm"模型还没有实现'add1'方法

en: no 'as.stepfun' method available for 'x'
zh: 没有适用于'x'的'as.stepfun'方法

en: no 'drop1' method for "mlm" models
zh: "mlm" 模型没有'drop1'方法

en: no 'getInitial' method found for "%s" objects
zh: 找不到"%s" 目标对象的'getInitial'方法

en: no 'time' or 'id' specified
zh: 没有设定'time'或'id'

en: no degrees of freedom for residuals
zh: 残差没有自由度

en: no factors in the fitted model
zh: 拟合模型里没有因子

en: no models to compare
zh: 没有可用来比较的模型

en: no observations informative at iteration
zh: 观察量不含信息于迭代

en: no replacement values supplied
zh: 没有设定替换值

en: no scores are available: refit with 'retx=TRUE'
zh: 没有分数: 用'retx=TRUE'重新进行拟合

en: no solution in the specified range of bandwidths
zh: 在设定的頻寬值域内找不到解答

en: no starting values supplied
zh: 没有设定初始值

en: no terms component
zh: 没有项组件

en: no terms in scope
zh: 範疇里没有项

en: no terms in scope for adding to object
zh: 加入目标对象时的範疇内没有项

en: no time series supplied
zh: 没有设定时间序列

en: no valid set of coefficients has been found: please supply starting values
zh: 找不到有效的係數：请提供初始值

en: non-NA residual length does not match cases used in fitting
zh: 非NA残差的长度与拟合时所用的案例不相符

en: non-factors ignored:
zh: 非因子略过不用:

en: non-finite 'bw'
zh: 'bw'是无限值

en: non-finite 'from'
zh: 'from'是无限值

en: non-finite 'to'
zh: 'to'是无限值

en: non-finite coefficients at iteration
zh: 係數值无限大于迭代

en: non-integer #successes in a binomial glm!
zh: binomial通用线性模型里出现了非整数的#成功!

en: non-integer counts in a binomial glm!
zh: binomial通用线性模型里出现了非整数的计数!

en: non-intersecting series
zh: 非相叉序列

en: non-leaf subtree of length 0
zh: 长度为0的非叶子树

en: non-matched further arguments are disregarded
zh: 不匹配的额外变元略过不用

en: non-positive values not allowed for the gamma family
zh: gamma分布族不允许有负值

en: non-square matrix
zh: 非正方形矩阵

en: non-stationary AR part
zh: 非平穩AR部分

en: non-stationary AR part from CSS
zh: CSS里有非平穩的AR部分

en: non-stationary seasonal AR part
zh: 非平穩季節性AR部分

en: non-stationary seasonal AR part from CSS
zh: CSS里有非平穩季節性的AR部分

en: non-time series not of the correct length
zh: 非时间序列的长度不对

en: not a valid "smooth.spline" object
zh:  "smooth.spline"目标对象不对

en: not a valid step function
zh: 步驟函数不对

en: not all series have the same frequency
zh: 不是所有的序列都有相同的頻率

en: not an unreplicated complete block design
zh: 不是非折疊完全区组设计

en: not enough 'x' data
zh: 'x'数据不够

en: not enough 'x' observations
zh: 'x'观察值数量不够

en: not enough 'y' data
zh: 'y'数据不够

en: not enough 'y' observations
zh: 'y'观察值数量不够

en: not enough (finite) 'x' observations
zh: (有限)'x'观察量数目不够

en: not enough data
zh: 数据不够

en: not enough degrees of freedom to define contrasts
zh: 设定对比的自由度不够

en: not enough finite observations
zh: 有限值的观察量不够

en: not enough groups
zh: 组个数不够

en: not enough observations
zh: 观察量不够

en: nothing to tabulate
zh: 没有可列表的数据

en: number of 'cutpoints' must be one less than number of symbols
zh: 'cutpoints'的数目必需比符号的数目小一个

en: number of 'cutpoints' must be one more than number of symbols
zh: 'cutpoints'的数目必需比符号的数目多一个

en: number of cluster centres must lie between 1 and nrow(x)
zh: 群集中心数目必需在1和nrow(x) 这间

en: number of differences must be a positive integer
zh: 差異数目必需是正整数

en: number of groups must be at least 2
zh: 组数至少为2

en: number of observations in 'x' and 'y' must match.
zh:  'x'和'y'里的观察量数目必需相等。

en: number of observations in each group must be at least 2
zh: 每组的观察量数目至少为2

en: number of offsets is %d should equal %d (number of observations)
zh: 偏置的个数是%d，应该同观察量的个数%d相等

en: number of offsets is %d, should equal %d (number of observations)
zh: 偏置的个数为%d，应该为%d (观察量数目)

en: number of rows in use has changed: remove missing values?
zh: 行数有变化：是不是删除了遺漏值?

en: number of series in 'object' and 'newdata' do not match
zh: 'object'和'newdata'里的序列数目不同

en: number of values supplied is not a sub-multiple of the number of values to be replaced
zh: 设定的值数目不是要替换值数目的倍数

en: number of weights = %d should equal %d (number of responses)
zh: weights = %d但应等于%d (反应数目)

en: number of weights must match number of observations.
zh: 重量数目必需和观察量数目相同。

en: numeric contrasts or contrast name expected
zh: 需要数值对比或对比的名字

en: object '%s' has no scores
zh: 目标对象'%s'没有分数

en: object must be of class "manova" or "maov"
zh: 目标对象必需是"manova"或"maov"的类别

en: object not interpretable as a factor
zh: 不能把目标对象解释成因子

en: observation(s) with NAs, NaNs and/or Infs deleted
zh: 删除了含NA, NaN或Inf的观察量

en: observations with 0 weight not used in calculating standard deviation
zh: 计算标准差时不用0重量的观察量

en: observations with 0 weights not used
zh: 不用0重量的观察量

en: observations with zero weight not used for calculating dispersion
zh: 计算离散度时0重量的观察量略过不用

en: one-diml optimization by Nelder-Mead is unreliable: use optimize
zh: 用Nelder-Mead方法来算1维优化不很可靠，用optimize

en: only 1-4 predictors are allowed
zh: 只允许有1到4个従属変数

en: only implemented for univariate time series
zh: 只适用于单变量时间序列

en: only univariate series are allowed
zh: 只允许单变量序列

en: option "show.coef.Pvalues" is invalid: assuming TRUE
zh: 選項"show.coef.Pvalues"不对: 假设成TRUE

en: option "show.signif.stars" is invalid: assuming TRUE
zh: 選項"show.signif.stars"不对: 假设成TRUE

en: or a 2 column matrix where col 1 is no. successes and col 2 is no. failures
zh: 或是有两个列的矩阵，第一列是成功的计数，第二列是失败的计数

en: orthogonal polynomials cannot be represented accurately enough for %d degrees of freedom
zh: 因为自由度为%d，所以无法准确地表达正交多項式

en: p-values may be incorrect
zh: p-值可能有错

en: parameter %s does not occur in the model formula | parameters %s do not occur in the model formula
zh[0]: 参数%s没有在模型公式里出现过

en: positive values only allowed for the inverse.gaussian family
zh: inverse.gaussian分布族只允许正值

en: possible convergence problem: optim gave code=
zh: 可能遇到了收斂问题：optim给了code=

en: prediction from a rank-deficient fit may be misleading
zh: 用秩缺乏拟合来进行预测的结果很可能不可靠

en: predictors must all be numeric
zh: 従属変数必需都是数值

en: probabilities cannot be negative nor all 0.
zh: 機率不能是负数，也不能全都是0。

en: probabilities must be non-negative.
zh: 機率必需为非负值。

en: probabilities must sum to 1.
zh: 機率总和必需为1。

en: read the documentation for 'trace' more carefully
zh: 请小心阅读'trace'说明书

en: ref = %d must be in 1:%d
zh: ref = %d必需在1:%d里

en: removed because response differs from
zh: 删除了，因为反应不同与

en: removed because response differs from model 1
zh: 被删除了，因为反应同模型1不相对

en: requested scores without an 'x' matrix
zh: 被要求的分数没有'x'矩阵

en: residual degrees of freedom in object suggest this is not an "lm" fit
zh: 目标对象的残差自由度表明这不是"lm" 拟合

en: residuals have rank
zh: 残差有秩

en: residuals have rank %d < %d
zh: 残差的秩 %d < %d

en: response not allowed in formula
zh: 公式里不能有反应

en: results are only valid up to model order
zh: 计算结果只适用于模型顺序

en: row dendrogram ordering gave index of wrong length
zh: 行系統樹圖排序索引结果的长度出了错

en: rows with zero weights not counted
zh: 0重量的行不算

en: sample is too sparse to find TD
zh: 样本太稀疏，找不到TD

en: sample is too sparse to find alph2
zh: 样本太稀疏，找不到alph2

en: sample size in each stratum must be > 1
zh: 每个阶层里的样本大小都必需 > 1

en: sample size must be between 3 and 5000
zh: 样本大小必需在3和5000之间

en: samples differ in location: cannot compute confidence set, returning NA
zh: 样本的位置不一样：无法计算置信集, 因此回覆NA

en: scatter plots only for univariate time series
zh: 散佈圖只适用于单变量时间序列

en: scope is not a subset of term labels
zh: 範疇不是项标记集的子集

en: seasonal MA part of model is not invertible
zh: 模型季節性的MA部分非可逆

en: series is not periodic or has less than two periods
zh: 序列没有周期，或其周期小于二

en: setVarying : vary length must match length of parameters
zh: setVarying : vary的长度必需同参数的长度相符

en: setting df = 1  __use with care!__
zh: 设定df = 1  小心使用!

en: singular contrast matrix
zh: 奇异对比矩阵

en: singular fit encountered
zh: 遇到了奇异拟合

en: singular gradient matrix at initial parameter estimates
zh: 参数初始估计值里有奇异梯度矩阵

en: singularities in regression
zh: 迴歸产生了奇异

en: singularities in the computation of the projection matrix
zh: 计算投影矩阵时出现了奇异点

en: size != sum(x), i.e. one is wrong
zh: size != sum(x), 两个中间至少有一个不对

en: some AR parameters were fixed: setting transform.pars = FALSE
zh: 一些AR参数是固定的：把transform.pars设成FALSE

en: some ARMA parameters were fixed: setting transform.pars = FALSE
zh: 一些ARMA参数是固定的：把transform.pars设成FALSE

en: some constant variables (%s) are really varying
zh: 某些恆量变量(%s) 其实在变动

en: some of the first %d eigenvalues are < 0
zh: %d个特征值小于0

en: some terms will have NAs due to the limits of the method
zh: 因为这个方法的限制，有些项的值为NA

en: some weights should be positive
zh: 至少有一些重量应该是正的

en: specified parametric for all predictors
zh: 所有従属変数都被设定为参数

en: specified the square of a factor predictor to be dropped when degree = 1
zh: degree = 1时不能忽略因子従属変数的二次方

en: specified the square of a predictor to be dropped with only one numeric predictor
zh: 只有一个数值従属変数时不能忽略従属変数的二次方

en: specify exactly one of 'k' and 'h'
zh: 'k'和'h'两者只能设定一个

en: specify exactly one of 'which' and 'x'
zh: 'which'和'x'两者只能设定一个

en: spline: first and last y values differ - using y[1] for both
zh: spline: 第一个和最后一个y的值不相等 -用y[1]

en: spline: invalid interpolation method
zh: spline: 内插方法不对

en: splinefun: invalid interpolation method
zh: splinefun: 内插方法不对

en: step size truncated due to divergence
zh: 因为算法分歧将步驟大小縮短

en: step size truncated: out of bounds
zh: 縮短了步驟大小：在值域外

en: stepfun: 'x' must be ordered increasingly
zh: stepfun: 'x'必需从小到大排序

en: sum(weights) != 1  -- will not get true density
zh:  sum(weights) != 1，因此无法取得真正的密度函数

en: supply both 'x' and 'y' or a matrix-like 'x'
zh: 要么同时设定'x'和'y'，要么只设定矩阵式的'x'

en: the 'height' component of 'tree' is not sorted
    (increasingly); consider applying as.hclust() first
zh: 'tree'里的'height'组件没有排序
    由小到大；应该先用as.hclust()

en: the 'se.fit' argument is not yet implemented for "mlm" objects
zh: 'se.fit'变元还没有为"mlm"目标对象实现

en: the 'split' argument must be a list
zh: 'split' 变元必需是串列

en: the contrast defined is empty (has no TRUE elements)
zh: 设定的对比是空的(不含任何TRUE值)

en: the first value of the time series must not be missing
zh: 时间序列的第一个数值不能遺漏

en: the following arguments to 'anova.glm' are invalid and dropped:
zh: 以下'anova.glm'的变元不对因此略过不用:

en: the series is entirely NA
zh: 时间序列里所有的值都是NA

en: there are %d Error terms: only 1 is allowed | there are %d Error terms: only 1 is allowed
zh[0]: 有%d个Error项，但最多只允许有1个

en: there are records with missing times, which will be dropped.
zh: 含遺漏时间的记录略过不用。

en: there must be at least 2 observations in each group
zh: 每组至少需要有两个观察量

en: this should not happen
zh: 这不应该发生

en: time series contains internal NAs
zh: 时间序列含内部NA

en: time series has no or less than 3 periods
zh: 時間序列的周期少于三

en: times to be replaced do not match
zh: 需要替换的时间不相符

en: too few cases, n < k
zh: 案例不够, n < k

en: too few distinct input values to fit a Michaelis-Menten model
zh: 因为相互不同的输入值太少，无法拟合Michaelis-Menten模型

en: too few distinct input values to fit a biexponential
zh: 因为相互不同的输入值太少，无法拟合biexponential

en: too few distinct input values to fit a four-parameter logistic
zh: 因为相互不同的输入值太少，无法拟合四个参数的逻辑斯特模型

en: too few distinct input values to fit a logistic model
zh: 因为相互不同的输入值太少，无法拟合逻辑斯特模型

en: too few distinct input values to fit an asymptotic regression model
zh: 无法拟合渐近迴歸模型，因为相互不同的输入值太少

en: too few distinct input values to fit the 'asympOff' model
zh: 因为相互不同的输入值太少，无法拟合'asympOff'模型

en: too few distinct input values to fit the 'asympOrig' model
zh: 因为相互不同的输入值太少，无法拟合'asympOrig'模型

en: too few distinct input values to fit the Gompertz model
zh: 因为相互不同的输入值太少，无法拟合Gompertz模型

en: too few distinct input values to fit the Weibull growth model
zh: 因为相互不同的输入值太少，无法拟合Weibull成长模型

en: too few groups
zh: 组数不够

en: too few non-missing observations
zh: 非遺漏的观察量数目不够

en: too few observations to fit an asymptotic regression model
zh: 观察量数目太小，无法拟合渐近迴歸模型

en: too many replacement values supplied
zh: 提供了太多的替换值

en: transformed ARMA parameters were fixed
zh: 变换过的ARMA参数是固定的

en: type '%s' is not implemented yet
zh: 还没有实现'%s'种类

en: type = "partial" is not yet implemented
zh: 还没有实现type="partial"的算法

en: unable to optimize from these starting value(s)
zh: 无法用这些初始值进行最佳化运算

en: unequal number of rows in 'cancor'
zh: 'cancor'里的行数不一样

en: univariate time series only
zh: 只适用于单变量时间序列

en: unknown bandwidth rule
zh: 没有这样的頻寬规则

en: unknown name(s) in the 'split' list
zh: 'split'串列里的名字不对

en: unknown named kernel
zh: 没有这样的内核名

en: unknown string value for s.window
zh: s.window所设定的字符串值不对

en: unrecognized control element(s) named `
zh: 没有叫这个名字的控制元素

en: upper scope does not include model
zh: 模型里没有上範疇

en: use only with "lm" objects
zh: 只对"lm"目标对象适用

en: using the %d/%d rows from a combined fit
zh: 在组合拟合中用%d/%d行

en: value of 'epsilon' must be > 0
zh: 'epsilon'的值必需 > 0

en: variable '%s' is absent, its contrast will be ignored
zh: 没有变量'%s'，因此它的对比略过不用

en: variable '%s' is not a factor
zh: 变量'%s'不是因子

en: variable '%s' was fitted with class "%s" but class "%s" was supplied
zh: 变量'%s'是由"%s"类别拟合而成，与提供的类别"%s"不相配

en: variables %s were specified with different classes from the fit
zh: 设定的变量%s的类别同拟合的类别不相符

en: we require a dendrogram
zh: 需要系統樹圖

en: weights must be non-negative and not all zero
zh: 重量必需为非负值，而且不能全部都为0

en: wrong embedding dimension
zh: 嵌入维度不对

en: wrong endrule
zh: endrule不对

en: wrong k / cs.ind
zh: k / cs.ind有错

en: wrong length for 'fixed'
zh: 'fixed'长度不对

en: wrong number of columns in 'x'
zh: 'x'里的列数不对

en: wrong number of contrast matrix rows
zh: 对比矩阵的行数不对

en: wrong number of predictors
zh: 従属変数数目不对

en: x is not a vector or univariate time series
zh: x不是向量或单变量时间序列

en: x$lag must have at least 1 column
zh: x$lag至少需要有1列

en: x[] and prob[] must be equal length vectors.
zh: x[]和prob[]必需是长度相等的向量。

en: y is empty or has only NAs
zh: y是空的或只含NA

en: y must be supplied.
    For density estimation use density()
zh: y必需存在。
    用density()来估计密度

en: y values must be 0 <= y <= 1
zh: y值必需满足0 <= y <= 1

en: y, groups and blocks must have the same length
zh: 'y', 'groups'和'blocks'的长度必需相同

en: you must supply 1 < df <= n,  n = #{unique x} =
zh: 你必需提供1 < df <= n,  n = #{unique x} =

en: zero non-NA points
zh: 无非NA数据点
