rrs.test {quantreg}R Documentation

Function to compute regression rankscore test of linear hypothesis

Description

Tests the hypothesis that b_1 = 0 in the quantile regression model

y = X_0 b_0 + X_1 b_1 + u

Usage

rrs.test(x0, x1, y, v, score="wilcoxon")

Arguments

x0 matrix of maintained regressors, a column of ones is appended automatically
x1 matrix of regressors under test
y response variable may be omitted if v is provided
v regression quantile structure from rq(x0,y)
score score function for test (see ranks())

Details

Value

sn Test statistic is asymptotically Chi-squared with rank(X1) degrees of freedom.
rank vector of ranks

Side Effects

References

[1] Gutenbrunner, C., J. Jureckova, Koenker, R. and Portnoy, S.(1993) "Tests of Linear Hypotheses based on Regression Rank Scores", Journal of Nonparametric Statistics, (2), 307-331.

[2] Koenker, R.W. and d'Orey (1994). "Remark on Alg. AS 229: Computing Dual Regression Quantiles and Regression Rank Scores", Applied Statistics, 43, 410-414.

See Also

rq, ranks

Examples

data(stackloss)
rrs.test(stack.x[,1:2],stack.x[,3],stack.loss)


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