Displaying 6 results from an estimated 6 matches for "qhat".
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2012 Jul 17
1
Threshold Quantile Regression code CRASHES in R
I am working on a two stage threshold quantile regression model in R, and my aim is to estimate the threshold of the reduced-form equation (call it rhohat), and the threshold of the structural equation (call it qhat), in two stages. On the first stage, i estimate rhohat by quantile regression and obtain the fitted values. I use these fitted values to estimate qhat on the second stage. The code is as follows (thanks to Prof. Bruce Hansen, whose code i modified): #***********************************************...
2013 Feb 14
2
Plotting survival curves after multiple imputation
...ct, method = "smallsample") {
if ((m <- length(object$analyses)) < 2)
stop("At least two imputations are needed for pooling.\n")
analyses <- object$analyses
k <- length(coef(analyses[[1]]))
names <- names(coef(analyses[[1]]))
qhat <- matrix(NA, nrow = m, ncol = k, dimnames = list(1:m,names))
u <- array(NA, dim = c(m, k, k),
dimnames = list(1:m, names, names))
for (i in 1:m) {
fit <- analyses[[i]]
qhat[i, ] <- coef(fit)
u[i, , ] <- vcov(fit)
}...
2013 Jan 30
3
Mac v Windows Mystery
...m with my quantreg package reported by a user doing censored quantile regression.
When he runs the test4.R file attached below (which reads the csv file also attached) on his windows machine he gets
an error like this:
> Error in dimnames(B) <- list(c("tau", dimnames(x)[[2]], "Qhat"), NULL) :
> length of 'dimnames' [1] not equal to array extent
> In addition: Warning message:
> In rbind(grid[1:J], B, qhat) :
> number of columns of result is not a multiple of vector length (arg 2)
However, when I run the same thing on my mac there is no error, no...
2007 May 17
1
MICE for Cox model
R-helpers:
I have a dataset that has 168 subjects and 12 variables. Some of the
variables have missing data and I want to use the multiple imputation
capabilities of the "mice" package to address the missing data. Given
that mice only supports linear models and generalized linear models (via
the lm.mids and glm.mids functions) and that I need to fit Cox models, I
followed the previous
2010 Feb 24
1
problem with looping on sqlSave()
...54545,
0.636363636363636, 0.727272727272727, 0.818181818181818, 0.909090909090909,
1, NA, NA, NA, NA, NA, NA, -14.571209, -13.829402, -22.1283685,
-22.717841, -34.8053215, 12.988246, 10.2528335, 9.47791, 24.585605,
NA, NA, NA, NA, NA, NA, NA), .Dim = c(11L, 3L), .Dimnames = list(
NULL, c("qhat", "lower", "upper"))), crit = 0.611274541966673,
numsig = 0L, pc = NA), .Names = c("m", "crit", "numsig",
"pc"))
> xlsFile <- odbcConnectExcel("file.xls", readOnly=F)
> for (i in 1:4){
sqlSave(xlsFile, as.dat...
2011 Oct 05
0
Which function for this?
...te 1, if they're all 0 or less, I write 0, so
0.05 0.13 1.2 0 0 0 0 0 red 1
0 0 0 0 0 0 0 0 white 0
0 0.06 0 0 0 0 0 0 blue 1
I want to understand if the value of the new variable (1 or 0) is correlated
to the colour.. I can use chi-square and what else? Anova and qhat else?
And to correlated the first 8 columns to the colour, can I use logit?
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