rrs.test {quantreg} | R Documentation |
Tests the hypothesis that b_1 = 0 in the quantile regression model
y = X_0 b_0 + X_1 b_1 + u
rrs.test(x0, x1, y, v, score="wilcoxon")
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()) |
sn |
Test statistic is asymptotically Chi-squared with rank(X1) degrees of freedom. |
rank |
vector of ranks |
[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.
rq, ranks
data(stackloss) rrs.test(stack.x[,1:2],stack.x[,3],stack.loss)