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In R  : modeGlob <- lm(rnorm(100)~ abs(rnorm(100))) #Your model

    modeGlob <- lm(rnorm(100)~ abs(rnorm(100))) #Your model.

    hii <- hatvalues(modeGlob) # hat matrix.

    rst <- modeGlob$residuals / (summary(modeGlob)$sigma * sqrt(1-hii)) # manually calculate standardized residuals.

    identical(rstandard(modeGlob) , rst) #[1]# check, this must be TRUE.

    plot(rstandard(modeGlob) , rst) # check it graphically.

In R: modeGlob <- lm(rnorm(100)~ abs(rnorm(100))) #Your model

    hii <- hatvalues(modeGlob) # hat matrix

    rst <- modeGlob$residuals / (summary(modeGlob)$sigma * sqrt(1-hii))

    identical(rstandard(modeGlob) , rst) #[1] TRUE

    plot(rstandard(modeGlob) , rst) # check it graphically

In R  :

    modeGlob <- lm(rnorm(100)~ abs(rnorm(100))) #Your model.

    hii <- hatvalues(modeGlob) # hat matrix.

    rst <- modeGlob$residuals / (summary(modeGlob)$sigma * sqrt(1-hii)) # manually calculate standardized residuals.

    identical(rstandard(modeGlob) , rst) # check, this must be TRUE.

    plot(rstandard(modeGlob) , rst) # check it graphically.
1
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In R: modeGlob <- lm(rnorm(100)~ abs(rnorm(100))) #Your model

    hii <- hatvalues(modeGlob) # hat matrix

    rst <- modeGlob$residuals / (summary(modeGlob)$sigma * sqrt(1-hii))

    identical(rstandard(modeGlob) , rst) #[1] TRUE

    plot(rstandard(modeGlob) , rst) # check it graphically