vcov
Variance-Covariance Matrix of the Estimated Coefficients

### Description

Computes the variance-covariance matrix of the estimated coefficients in a fitted model object.

### Usage

    vcov(object, ...)
    ## S3 method for class 'lm':
    vcov(object, ...)
    ## S3 method for class 'glm':
    vcov(object, ...)
    ## S3 method for class 'mlm':
    vcov(object, ...)
    ## S3 method for class 'nls':
    vcov(object, ...)
    ## S3 method for class 'summary.lm':
    vcov(object, ...)
    ## S3 method for class 'summary.glm':
    vcov(object, ...)

### Arguments

object | a fitted model object.
... | other optional arguments pass to the method.

### Details

This is a generic function, and several invisible methods have been implemented for classes Arima, lm, mlm, glm, nls, summary.lm and summary.glm.
of object.
For vcov.lm, it returns a matrix, that is square of component sigma multiply component cov.unscaled of the summary's result of object.
For vcov.mlm, it returns Kronecker products of estimated variance of object and the component cov.unscaled of the first element of summary's result of object.
For vcov.glm, it returns the component cov.scaled of the summary's result of object.
For vcov.nls, it returns a matrix, that is component cov.unscaled multiply square of component sigma of the summary's result of object.
vcov.summary.lm andvcov.summary.glm are very similar to vcov.lm and vcov.glm, respectively. The only difference is that the argument object is already a summary's result.
Value
returns the variance-covariance matrix of the estimated coefficients in the fitted model object.
Examples

    # example for vcov.lm
    lmfit <- lm(ozone ~ wind + temperature + radiation,
        data=Sdatasets::air)
    vcov(lmfit)
    # example for vcov.summary.lm
    vcov(summary.lm(lmfit))
    # example for vcov.glm
    glmfit <- glm(Kyphosis ~ Age + Number, family=binomial,
        data=Sdatasets::kyphosis)
    vcov(glmfit)
    # example for vcov.summary.glm
    vcov(summary.glm(glmfit))
    # example for vcov.mlm
    ymat <- with(Sdatasets::fuel.frame, cbind(Fuel, Mileage))
    vcov(lm(ymat ~ Disp. + Weight, data=Sdatasets::fuel.frame))

    # example for vcov.nls
    vcov(nls(circumference ~ A/(1 + exp(-(age-B)/C)), data = Sdatasets::Orange,
        start = list(A=150, B=600, C=400)))

Package stats version 6.1.5-18
Package Index