sm (version 2.2-6.0)

sm.sigma2.compare: Comparison across two groups of the error standard deviation in nonparametric regression with two covariates.

Description

This function compares across two groups, in a hypothesis test, the error standard deviation in nonparametric regression with two covariates.

Usage

sm.sigma2.compare(x1, y1, x2, y2)

Value

a p-value for the test of equality of standard deviations.

Arguments

x1

a two-column matrix of covariate values for group 1.

y1

a vector of responses for group 1.

x2

a two-column matrix of covariate values for group 2.

y2

a vector of responses for group 2.

Side Effects

none.

Details

see the reference below.

References

Bock, M., Bowman, A.W. & Ismail, B. (2007). Estimation and inference for error variance in bivariate nonparametric regression. Statistics & Computing, to appear.

See Also

sm.sigma

Examples

if (FALSE) {
with(airquality, {
   x     <- cbind(Wind, Temp)
   y     <- Ozone^(1/3)
   group <- (Solar.R < 200)
   sig1 <- sm.sigma(x[ group, ], y[ group], ci = TRUE)
   sig2 <- sm.sigma(x[!group, ], y[!group], ci = TRUE)
   print(c(sig1$estimate, sig1$ci))
   print(c(sig2$estimate, sig2$ci))
   print(sm.sigma(x[ group, ], y[ group], model = "constant", h = c(3, 5))$p)
   print(sm.sigma(x[!group, ], y[!group], model = "constant", h = c(3, 5))$p)
   print(sm.sigma2.compare(x[group, ], y[group], x[!group, ], y[!group]))
})
}