similar to: Solving binary integer optimization problem

Dear R users/developers I requested help to solve the problem of formulating Multivariate Sample selection model by using Full Information Maximum Likelihood (FIML)estimation method. I could not get any response. I formulated the following code of FIML to analyse univariate sample selection problem. Would you please advise me where is my problem library (sem) library(nrmlepln) Selection

Dear guRus: I am using lmer for a mixed model that includes a random intercept for a set of effects that have the same distribution, Normal(0, sig2b). This set of effects is of variable size, so I am using an as.formula statement to create the formula for lmer. For example, if the set of random effects has dimension 8, then the lmer call is: Zs<-

Hola a todos, Me gustaria pedir vuestra ayuda a encontrar el error que no consigo encontrar en este archivo. He revisado todo mil veces y probado y no doy con ello.Adjunto el archivo con Google drive porque es muy grande. ? monicap_50.csv <https://docs.google.com/file/d/0B8o2KrPEgG7ATlBMc19lTVk1d3M/edit?usp=drive_web> ? Este es el script, y lo que no entiendo que pasa es que tengo 592044

Hi everone, I have a question on using lme on a mixed effects model. The linear mixed model is in the form of: y = bX +Zu + e where "X" and "Z" are the matrices, "b" is the coefficient vector of fixed effects, "u" is the coefficient vector of random effects, and e is an error vector. I would like to use "lme" function to fit the model and

I have a function called nnmf which takes in one matrix and returns two matrices. for example, > X [,1] [,2] [,3] [,4] [1,] 1 4 7 10 [2,] 2 5 8 11 [3,] 3 6 9 12 > z=nnmf(X,2) > z$W [,1] [,2] [1,] 0.8645422 0.6643681 [2,] 1.7411863 0.5377504 [3,] 2.6179287 0.4111063 > z$H [,1] [,2] [,3] [,4] [1,] 1.14299486

Dear all, I have a set of data with 4 inputs (independent variables) and one output (dependent variable). I want to perform a regression analysis in order to fit these data to a regression model, however due to the non-linearity of the model I do not have a clue which equation to use. I am thinking of starting with a very general equation including ^3 terms and interactions between the variables

Hi all, I have a data frame with "clustered" rows as follows: Cu1 x1 y1 z1 ... Cu1 x2 y2 z2 ... Cu1 x3 y3 z3 ... # end of first cluster Cu1 Cu2 x4 y4 z4 ... Cu2 x5 y5 z5 Cu2 ... # end of second cluster Cu2 Cu3 ... ... "cluster"-size is 3 in the example above (rows making up a cluster are always consecutive). Is there any faster way to sample n clusters (with

I am trying to do a surface profile plot. data is X                  Y(1)             Z(1) 1-jan-02       2002        number 2-jan-02       2002        number . . . 1-jan-03       2003 (Y2)     number Z(2) 2-jan-03       2003 (Y2)     number Z(2) . . . until dec 31 2007.   I used the plot3d funtions to build a scatter point plot. Call rinterface.rrun("library(rgl)") Call

Ralf, et al., Attached is the latest version of my autovectorization patch. llvmdev has been CC'd (as had been suggested to me); this e-mail contains additional benchmark results. First, these are preliminary results because I did not do the things necessary to make them real (explicitly quiet the machine, bind the processes to one cpu, etc.). But they should be good enough for discussion.

On Sat, 2011-10-29 at 12:30 -0500, Hal Finkel wrote: > Ralf, et al., > > Attached is the latest version of my autovectorization patch. llvmdev > has been CC'd (as had been suggested to me); this e-mail contains > additional benchmark results. > > First, these are preliminary results because I did not do the things > necessary to make them real (explicitly quiet the

Dear R experts/ users Full Information Maximum Likelihood (FIML) estimation approach is considered robust over Seemingly Unrelated Regression (SUR) approach for analysing data of multivariate sample selection problem. The zero cases in my dependent variables are resulted from three sources: Irreverent options, not choosing due to negative utility and not used in the reported time. FIML can

On Sat, 2011-10-29 at 15:16 -0500, Hal Finkel wrote: > On Sat, 2011-10-29 at 14:02 -0500, Hal Finkel wrote: > > On Sat, 2011-10-29 at 12:30 -0500, Hal Finkel wrote: > > > Ralf, et al., > > > > > > Attached is the latest version of my autovectorization patch. llvmdev > > > has been CC'd (as had been suggested to me); this e-mail contains > >

Dear list, I was curious how to subtract a vector from matrix? Say, I have mat <- matrix(1:40, nrow=20, ncol=2) x <-c(1,2) I want, x-mat[1,] and x-mat[2,], and so on... Basically, subtract column elements of x against column elements in mat. But x-mat won't do it. Thanks, Mike [[alternative HTML version deleted]]

On Sat, 2011-10-29 at 14:02 -0500, Hal Finkel wrote: > On Sat, 2011-10-29 at 12:30 -0500, Hal Finkel wrote: > > Ralf, et al., > > > > Attached is the latest version of my autovectorization patch. llvmdev > > has been CC'd (as had been suggested to me); this e-mail contains > > additional benchmark results. > > > > First, these are preliminary

Dear All, I am trying to perform MANOVA. I have table with 504 columns(species) and 36 rows) with two grouping (season and location) Zx <- Z[c(4:504)] Zxm <- as.matrix(Z) m<- manova(Zxm~Season*location, data=Z) when I do summary.aov, I get respond for each species but summary.manova summary.manova(m) :" residuals have rank" 24<501. What can it be the reason for this error

HI Jim and all, I want to put one more condition. Include col2 and col3 if they are not in col1. Here is the data mydat <- read.table(textConnection("Col1 Col2 col3 K2 X1 NA Z1 K1 K2 Z2 NA NA Z3 X1 NA Z4 Y1 W1"),header = TRUE,stringsAsFactors=FALSE) The desired out put would be Col1 Col2 col3 1 X1 0 0 2 K1 0 0 3 Y1 0 0 4 W1 0 0 6 K2 X1

Jim has been exceedingly patient (and may well continue to be so), but this smells like "failure to launch". At what point will you start showing your (failed) attempts at solving your own problems so we can help you work on your specific weaknesses and become self-sufficient? -- Sent from my phone. Please excuse my brevity. On February 25, 2018 7:55:55 AM PST, Val <valkremk at

Hi Val, My fault - I assumed that the NA would be first in the result produced by "unique": mydat <- read.table(textConnection("Col1 Col2 col3 Z1 K1 K2 Z2 NA NA Z3 X1 NA Z4 Y1 W1"),header = TRUE,stringsAsFactors=FALSE) val23<-unique(unlist(mydat[,c("Col2","col3")])) napos<-which(is.na(val23)) preval<-data.frame(Col1=val23[-napos],

Hi,   I use fCopulae package to draw different graphs of univariate and bivariate skew t.  But the plots titles overlap.  I tried using cex.main, font.main to adjust the size but they still overlaps.  Here is my code: par(mfrow = c(3, 1)) mu = 0 Omega = 1 alpha1 = 0 alpha2 = 1.5 alpha3 = 2 alpha4 = 0.5 Z1 = matrix(dmvst(x, 1, mu, Omega, alpha1, df = Inf), length(x)) Z2 = matrix(dmvst(x, 1, mu,

Thank you Jim, I read the data as you suggested but I could not find K1 in col1. rbind(preval,mydat) Col1 Col2 col3 1 <NA> <NA> <NA> 2 X1 <NA> <NA> 3 Y1 <NA> <NA> 4 K2 <NA> <NA> 5 W1 <NA> <NA> 6 Z1 K1 K2 7 Z2 <NA> <NA> 8 Z3 X1 <NA> 9 Z4 Y1 W1 On Sat, Feb 24, 2018 at 6:18 PM, Jim