R: Comparison across two groups of the error standard deviation...

sm.sigma2.compare {sm} | R Documentation

## 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)

### 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.

### Details

see the reference below.

### Value

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

### Side Effects

none.

### 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

    ## Not run:
    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]))
    })

    ## End(Not run)

[Package sm version 2.2-5.4 Index]