search for: esitmate

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

hello for exampl, i have this programme # Generating data which are right truncated library(DTDA) library(splines) library(survival) n<-25 X<-runif(n,0,1) V<-runif(n,0.75,1) for (i in 1:n){ while (X[i]>V[i]){ X[i]<-runif(1,0,1) V[i]<-runif(1,0.75,1) }} res<-lynden(X=X,U=NA, V=V, boot=TRUE) attach(res) temps = time M_i = n.event L_t = res

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 mode...

> On May 12, 2018, at 9:42 AM, malika yassa via R-help <r-help at r-project.org> wrote: > > > hello > for exampl, i have this programme > # Generating data which are right truncated > library(DTDA) > library(splines) > library(survival) > n<-25 > X<-runif(n,0,1) > V<-runif(n,0.75,1) > for (i in 1:n){ > while (X[i]>V[i]){ >

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

hello > p(X ? V) diffetente zero > look this > Let X and V be two independent random variables with unknow >? distribution functions (d.f.?s) F and G respectively. Under truncation from the right we observe (X, Z) only if X ? Z > I simulate X and Z and I use Lynden bell estimation > I need now to calculate alpha =p(X ? V)but no p(X ? V)=0 >? > > > > > >

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