similar to: Graphic representation of model results

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,

Hi, I am new to R for solving optimization problems, I have set of communication channels with limited capacity with two types of costs, fixed and variable cost. Each channel has expected gain for a single communication. I want to determine optimal number of communications for each channel maximizing ROI)return on investment) with overall budget as constraint.60000 is the budget allocated.

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 Val, Your problem seems to be that the data are read in as a factor. The simplest way I can think of to get around this is: mydat <- read.table(textConnection("Col1 Col2 col3 Z1 K1 K2 Z2 NA NA Z3 X1 NA Z4 Y1 W1"),header = TRUE,stringsAsFactors=FALSE) preval<-data.frame(Col1=unique(unlist(mydat[,c("Col2","col3")]))[-1], Col2=NA,col3=NA) rbind(preval,mydat)

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

Sorry , I hit the send key accidentally here is my complete message. Thank you Jim and all, I got it. I have one more question on the original question What does this "[-1] " do? preval<-data.frame(Col1=unique(unlist(mydat[,c("Col2","col3")]))[-1], Col2=NA,col3=NA) mydat <- read.table(textConnection("Col1 Col2 col3 Z1 K1 K2 Z2

Thank you Jim and all, I got it. I have one more question on the original question What does this "[-1] " do? preval<-data.frame(Col1=unique(unlist(mydat[,c("Col2","col3")]))[-1], Col2=NA,col3=NA) mydat <- read.table(textConnection("Col1 Col2 col3 Z1 K1 K2 Z2 NA NA Z3 X1 NA Z4 Y1 W1"),header = TRUE)

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 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

I have a matrix for which each row has 12 elements that represent the xyz coordinates of 4 points. So each row of M is (x1,y1,z1,x2,y2,z2,x3,y3,z3,x4,y4,z4). Some points have NA as z values. I want another matrix to be the same as M but with the coordinates of those points with z=NA placed last. For ezample if z1=NA then the new matrix row should be (x2,y2,z2,x3,y3,z3,x4,y4,z4,x1,y1,z1)

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<-

On 24/02/2018 1:53 PM, William Dunlap via R-help wrote: > x1 = rbind(unique(preval),mydat) > x2 <- x1[is.na(x1)] <- 0 > x2 # gives 0 > > Why introduce the 'x2'? x1[...] <- 0 alters x1 in place and I think that > altered x1 is what you want. > > You asked why x2 was zero. The value of the expression > f(a) <- b > and assignments

hello I make a subroutine that give-me a (mathematical) function in string format. I would like transform this string into function ( R function ). thanks for any tips. cleber #e.g. fun_String = "-100*x1 + 0*x2 + 100*x3" fun <- function(x1,x2,x3){ return( ############ evaluation( fun_String ) ############ ) True String mathematical function :-( :-( > nomes [1]

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

Hi, R users, I'm trying to transform a matrix A into B (see below). Anyone knows how to do it in R? Thanks. Matrix A (zone to zone travel time) zone z1 z2 z3 z1 0 2.9 4.3 z2 2.9 0 2.5 z3 4.3 2.5 0 B: from to time z1 z1 0 z1 z2 2.9 z1 z3 4.3 z2 z1 2.9 z2 z2 0 z2 z3 2.5 z3 z1 4.3 z3 z2 2.5 z3 z3 0 The real matrix I have is much larger, with more than 2000 zones. But I think it should

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

Hello all R-users _question 1_ I need to make a statistical model and respective ANOVA table but I get distinct results for the T-test (in summary(lm.object) function) and the F-test (in anova(lm.object) ) shouldn't this two approach give me the same result, i.e to indicate the same significants terms in both tests??????? obs. The system has two restrictions: 1) sum( x_i ) = 1 2) sum(

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