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Rev 75334 Rev 83579
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roller.glm <- glm(weight~depression, data=roller, weights= 1:10)
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roller.glm <- glm(weight~depression, data=roller, weights= 1:10)
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roller.glm0<- glm(weight~depression, data=roller, weights= 0:9)
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roller.glm0<- glm(weight~depression, data=roller, weights= 0:9)
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predict(roller.glm0, type="terms")# failed till 2003-03-31
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predict(roller.glm0, type="terms")# failed till 2003-03-31
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## FIXME : glm()$residual [1] is NA,  lm()'s is ok.
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stopifnot(exprs = {
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## all.equal(residuals(roller.glm0, type = "partial"),
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    all.equal(residuals(roller.glm0, type = "partial"),
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##          residuals(roller.lm0,  type = "partial") )
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              residuals(roller.lm0,  type = "partial"), tol = 1e-14)  # 4.0e-16
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 - 
 
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 - 
 
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all.equal(deviance(roller.lm),
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    all.equal(deviance(roller.lm),
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          deviance(roller.glm))
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              deviance(roller.glm), tol = 1e-14) # 2.4e-16
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all.equal(weighted.residuals(roller.lm),
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    all.equal(weighted.residuals(roller.lm),
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          residuals         (roller.glm))
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              residuals         (roller.glm), tol = 2e-14) # 9.17e-16
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 - 
 
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all.equal(deviance(roller.lm0),
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    all.equal(deviance(roller.lm0),
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          deviance(roller.glm0))
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              deviance(roller.glm0), tol = 1e-14) # 2.78e-16
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all.equal(weighted.residuals(roller.lm0, drop=FALSE),
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    all.equal(weighted.residuals(roller.lm0, drop=FALSE),
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          residuals         (roller.glm0))
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              residuals         (roller.glm0),  tol = 2e-14) # 6.378e-16
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})
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(im.lm0 <- influence.measures(roller.lm0))
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(im.lm0 <- influence.measures(roller.lm0))
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- 
 
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stopifnot(exprs = {
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all.equal(unname(im.lm0 $ infmat),
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    all.equal(unname(im.lm0 $ infmat),
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          unname(cbind(  dfbetas      (roller.lm0)
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              unname(cbind(  dfbetas      (roller.lm0)
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                       , dffits       (roller.lm0)
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                         , dffits       (roller.lm0)
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                       , covratio     (roller.lm0)
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                         , covratio     (roller.lm0)
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                       ,cooks.distance(roller.lm0)
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                          ,cooks.distance(roller.lm0)
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                       ,lm.influence  (roller.lm0)$hat)
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                          ,lm.influence  (roller.lm0)$hat)
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                 ))
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                     ))
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 - 
 
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all.equal(rstandard(roller.lm9),
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    all.equal(rstandard(roller.lm9),
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          rstandard(roller.lm0),tolerance = 1e-14)
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              rstandard(roller.lm0),tolerance = 1e-14)
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all.equal(rstudent(roller.lm9),
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    all.equal(rstudent(roller.lm9),
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          rstudent(roller.lm0),tolerance = 1e-14)
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              rstudent(roller.lm0),tolerance = 1e-14)
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all.equal(rstudent(roller.lm),
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    all.equal(rstudent(roller.lm),
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          rstudent(roller.glm))
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              rstudent(roller.glm))
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all.equal(cooks.distance(roller.lm),
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    all.equal(cooks.distance(roller.lm),
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          cooks.distance(roller.glm))
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              cooks.distance(roller.glm))
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 - 
 
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all.equal(summary(roller.lm0)$coefficients,
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    all.equal(summary(roller.lm0)$coefficients,
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          summary(roller.lm9)$coefficients, tolerance = 1e-14)
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              summary(roller.lm9)$coefficients, tolerance = 1e-14)
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all.equal(print(anova(roller.lm0), signif.st=FALSE),
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    all.equal(print(anova(roller.lm0), signif.st=FALSE),
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                anova(roller.lm9), tolerance = 1e-14)
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                    anova(roller.lm9), tolerance = 1e-14)
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})
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###  more regression tests for lm(), glm(), etc :
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###  more regression tests for lm(), glm(), etc :
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## moved from ?influence.measures:
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## moved from ?influence.measures:
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lm.SR <- lm(sr ~ pop15 + pop75 + dpi + ddpi, data = LifeCycleSavings)
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lm.SR <- lm(sr ~ pop15 + pop75 + dpi + ddpi, data = LifeCycleSavings)
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(IM <- influence.measures(lm.SR))
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(IM <- influence.measures(lm.SR))
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summary(IM)
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summary(IM)
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## colnames will differ in the next line
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## colnames will differ in the next line
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stopifnot(
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all.equal(dfbetas(lm.SR), IM$infmat[, 1:5], check.attributes = FALSE,
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    all.equal(dfbetas(lm.SR), IM$infmat[, 1:5], check.attributes = FALSE,
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          tolerance = 1e-12)
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              tolerance = 1e-12)
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)
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signif(dfbeta(lm.SR), 3)
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signif(dfbeta(lm.SR), 3)
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covratio (lm.SR)
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covratio (lm.SR)
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## Multivariate lm ("mlm") --- Example from  ?SSD
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## Multivariate lm ("mlm") --- Example from  ?SSD
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reacttime <- matrix(c(
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reacttime <- matrix(c(