# sm.sigma2.compare: Comparison across two groups of the error standard deviation... In sm: Smoothing Methods for Nonparametric Regression and Density Estimation

 sm.sigma2.compare 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.

none.

### References

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

`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)```

sm documentation built on July 4, 2022, 5:06 p.m.