Plot fitted model diagnostics

Plot fitted model diagnostics such as residuals vs fitted values, quantile-quantile, scale-location, Cook's distance, residuals vs leverage, Cook's distance vs leverage, a fitted spatial covariance function, and a fitted anisotropic level curve of equal correlation.

# S3 method for splm
plot(x, which, ...)

# S3 method for spautor
plot(x, which, ...)

# S3 method for spglm
plot(x, which, ...)

# S3 method for spgautor
plot(x, which, ...)

Arguments

x

A fitted model object from splm(), spautor(), spglm(), or spgautor().

which

An integer vector taking on values between 1 and 7, which indicates the plots to return. Available plots are described in Details. If which has length greater than one, additional plots are stepped through in order using <Return>. The default for splm() and spglm() fitted model objects is which = c(1, 2, 7). The default for spautor() and spgautor() fitted model objects is which = c(1, 2).

...

Other arguments passed to other methods.

Value

No return value. Function called for plotting side effects.

Details

For all fitted model objects,, the values of which make the corresponding plot:

• 1: Standardized residuals vs fitted values (of the response)

• 2: Normal quantile-quantile plot of standardized residuals

• 3: Scale-location plot of standardized residuals

• 4: Cook's distance

• 5: Standardized residuals vs leverage

• 6: Cook's distance vs leverage

For splm() and spglm() fitted model objects, there are two additional values of which:

• 7: Fitted spatial covariance function vs distance

• 8: Fitted anisotropic (or isotropic) level curve of equal correlation

Examples

spmod <- splm(z ~ water + tarp,
  data = caribou,
  spcov_type = "exponential", xcoord = x, ycoord = y
)
plot(spmod)



plot(spmod, which = c(1, 2, 4, 6))