search for: esitm

Hi, I am about to write functions for multivariate kernel densitiy estimation with mixed categorical and continuous date (accoring to Jeff Racine and Qi Li), and the leave-one-out window esitmation needs a lot of computation. I am now optimizing the code performance and therefore fhe following questions: As R uses call-by-value for functions, is it computational expensive to pass large matrices in function arguments? (i.e. are they really copied and does this need much computing time?)...

...=NA, V=V, boot=TRUE) attach(res) temps = time M_i = n.event L_t = res F_t=1-L_t??????????????????????????????????? ? par(mfrow=c(1,1)) plot(L_t$time,L_t$survival,type="s",lty=2:3,lwd=2,las=1,cex.lab=1.1,font.lab=2,col="red",xlab="temps",ylab="L(t)",main="Esitmation de la Fonction de Survie L(t)") i need to calculate the probability p(X>V) Le jeudi 10 mai 2018 ? 17:15:06 UTC+2, John Kane <jrkrideau at yahoo.ca> a ?crit : We need some idea of the problem. http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducibl...

Dear R users, I have panel data on the amount of money spent by travellers from 8 origin countries in 4 destinations. I would like to carry out analysis for destinations, origins and time. However, it seems to me that the package "plm" can only esitmate two-way panel data (indexed by a two-dimensional array). Any suggestions would be greatly appreciated. Thank you. Best regards, Danice [[alternative HTML version deleted]]

...Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -1.7782 0.5948 -2.990 0.004879 ** x_var 2.1237 0.5073 4.187 0.000162 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 I can get the esitmates (i.e. -1.7782 and 2.1237) of coefficients by calling results$coefficients But I don't know how to get the corresponding t values and P values for those coefficients. I am running a lot of regression models and I can not run 'summary' every time to get the t and P values for each m...

...on, this may be what you are seeking. It's the Pr( X > t ) > > par(mfrow=c(1,1)) > plot(L_t$time,L_t$survival,type="s",lty=2:3,lwd=2,las=1,cex.lab=1.1,font.lab=2,col="red",xlab="temps",ylab="L(t)",main="Esitmation de la Fonction de Survie L(t)") > > > i need to calculate the probability p(X>V) As I see it the probability of X>V is: sum(X > V) [1] 0 And I see this as a matter of definition. I'm guessing you wanted the estimated Hazard. If I'm wrong, I wonder if you can...

We need some idea of the problem. http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example http://adv-r.had.co.nz/Reproducibility.html On Thursday, May 10, 2018, 11:07:30 a.m. EDT, malika yassa via R-help <r-help at r-project.org> wrote: Hello Do You help me, i have the problem in the package DTDA for ?find the probability of truncation

...ent > > L_t = res > > F_t=1-L_t? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? > > par(mfrow=c(1,1)) > > plot(L_t$time,L_t$survival,type="s",lty=2:3,lwd=2,las=1,cex.lab=1.1,font.lab=2,col="red",xlab="temps",ylab="L(t)", > > > main="Esitmation de la Fonction de Survie L(t)") [[alternative HTML version deleted]]

Hi all, I ran a discriminant analysis with some data and want to get a general idea of prediction error rate. Some have suggested using X-fold cross validation procedure. Anyone know if there is a function for this in R? Thanks, Wade [[alternative HTML version deleted]]

I hope this list is small enough for not beeing banned when introducing oneself. So... Hi, I just subscribed to the theora-lists. I'm from the XVID project, so I know a deal about video and MPEG-4 in particular, but nothing about Vorbis/Theora etc., That's why I'm here, because I'm interested in patent-free alternatives. I guess there is no documentation of the current status