Description Usage Arguments Details Value Side Effects References See Also Examples

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

1 | ```
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.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
## 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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