search for: llim

Dear researchers I wish to plot a box plot without the mean line (the black line) and plot only the mean (red square). Futhermore, is it possible to add standard error and/or stadard deviation? This is an example mytest <- c(2.1,2.6,2.7,3.2,4.1,4.3,5.2,5.1,4.8,1.8,1.4,2.5,2.7,3.1,2.6,2.8) boxplot(mytest,lty = "solid") means <- mean(mytest,na.rm=TRUE) points(means, pch = 22, col

...et the x value in order to plot them? package(ecodist) X<-1:100 Y<-rnorm(1:100) Z<-rnorm(1:100) XY<-dist(data.frame(X,Y)) YX<-dist(data.frame(Y,X)) my.mgram<-mgram(XY,XZ) plot(my.mgram) print(my.mgram) > print(my.mgram) $mgram lag ngroup mantelr pval llim ulim [1,] 3.770055 672 0.500012737 0.001 0.49689923 0.504301550 [2,] 11.310165 691 0.383960457 0.001 0.38000201 0.387324434 [3,] 18.850274 584 0.232086251 0.001 0.22670074 0.237501735 [4,] 26.390384 587 0.114097397 0.001 0.10243901 0.122973735 [5,] 33.9304...

I have the following problem. inf p= Int [dnorm(x-d) * pnorm(x) ^ (m-1)] dx -inf Given p and m, I want to find d. For example, p m d .9 2 1.81 Is there a way to solve this problem in R? Ideally I would have a function with arguments p and m, and output d. Thanks very much for any help. Bill -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing

Hi :) Was just wondering whether someone could help me with adjustments to trellis plots (parallel). I've got two way multivariate data. I want to make parallel plots for one of the factors, and want to color the lines according to the other factor. The first thing I manage, but with the other I'm lost :( Can only change the overall color. This is basically how far I get:

...es(cbind(x,y,yhat)) # Add a constant to x (for alpha) x=cbind(1,x) # "normalization" fun to make the rest of the x's add up to 1 normalize=function(x)c(x[1], x[2:length(x)]/sum(x[2:length(x)])) # objective function: fn=function(ws){ ws=normalize(ws) sum((x %*% ws - yhat)^2)} llim = c(-Inf,rep(0,ncol(x)-1)) # alpha (col 1 of 'x') is -Inf to Inf ulim = c( Inf,rep(1,ncol(x)-1)) # betas (cols 2:4 of 'x') are 0 to 1 th=matrix(c(0,rep(1/3,3))) o = optim(th, fn, method="L-BFGS-B",lower=llim, upper=ulim) o REALPAR = normalize(o$par) REALPAR [[alternativ...

...r running in the 32 bits version. The problem comes from the mle function, using it with a lower constrain. In 64 bits version it works fine but when I put it in the R 32 bits it fails. (same numbers, all equal!) The call is: *mle(minuslogl = p.est,start = beta,method = "L-BFGS-B",lower=llim*reduction)* lower = -0.01570427 The optimizer (optim function in 32 bits) display: -0.015704 -loglik 48.690236 -0.015704 -loglik 48.690236 -0.017704 -loglik 1.#QNAN0 And it is not respecting the lower constrain. Could anyone explain me why this? Maybe I am misunderstunding of lower parameter me...

...esults2. Notice that column 1 does not have a column heading. Tresults2: [,1] estparam 18.00000 nullval 20.00000 . . . ciWidth 2.04622 HalfInterval 1.02311 pertinent code: results<-cbind( estparam, nullval, t, pv_left, pv_right, pv_two_t, estse, df, cc, tbox, llim, ulim, ciWidth, HalfInterval) tresults<-round((results),5) tresults2<-data.frame(t(tresults)) names(tresults2)<-c("Statistic ", "Value") tresults2 =========================================================================================== After transposing my dataframe...

Dear List, I am looking to plot error bars on a line using dispersion. I have values for the upper value and for the lower values, however i am unsure how to plot different values for the upper CI and the lower CI? I have been using dispersion(1:35,sim,simCI,col="red") Where there are 35 points, and simCI relates to a vector containing the lower confidence intervals, however i want

...> The problem comes from the mle function, using it with a lower constrain. > In 64 bits version it works fine but when I put it in the R 32 bits it > fails. (same numbers, all equal!) > > The call is: > *mle(minuslogl = p.est,start = beta,method = > "L-BFGS-B",lower=llim*reduction)* > lower = -0.01570427 > > The optimizer (optim function in 32 bits) display: > -0.015704 -loglik 48.690236 > -0.015704 -loglik 48.690236 > -0.017704 -loglik 1.#QNAN0 > > And it is not respecting the lower constrain. > > Could anyone explain me why this?...

...00,20) > z<-sample(1:1000,20) > M1<-as.matrix( distance(x)) > M2 <-as.matrix( distance(y )) > M3<-as.matrix( distance(z )) > D1<-(lower(M1)) > D2<-(lower(M2)) > D3<-(lower(M3)) > mantel(D1 ~ D2+D3, nperm=1000) mantelr pval1 pval2 pval3 llim.2.5% ulim.97.5% 0.09014696 0.10300000 0.89800000 0.18400000 0.01857311 0.18468621 > partial.mantel.test(M1,M2,M3,quiet=T) $MantelR r12 r13 r23 r12.3 r13.2 0.08977575 0.02170997 -0.01561346 0.09014696 0.02320821 $p [1] 0.09590410 0.30769231 0.47552448...

Dear Dr.Goslee and anyone may intrested in matrix manipulate, I am using your ecodist to do mantel and partial mantel test, I have locality data and shape variation data, and the two distance matrixs are given as belowings. When I run the analysis, it is always report that the matrix is not square, but I didn't know what's wrong with my data. Would you please help me on this. I am quite

Got problems with plotCI (plotrix) I only want to plot the upper part of the error bar in my barplot I had the exact same commands working two months ago Now I wanted to change the legend and when I ran it again plotCI stopped working. To me it seems like there must some bug in R library(plotrix) library (graphics) x = matrix(c( 13.75516276, 3.944604404,