sm.sigma2.compare | R Documentation |

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

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

`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. |

see the reference below.

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

none.

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

`sm.sigma`

## 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)

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