search for: 0.920

If I have a table (we'll call it, "test") containing two columns (as below): i x1 x2 x3 x4 x5 y 0 1.125 0.232 7.160 0.0859 8.905 1.5563 7 0.920 0.268 8.804 0.0865 7.388 0.8976 15 0.835 0.271 8.108 0.0852 5.348 0.7482 22 1.000 0.237 6.370 0.0838 8.056 0.7160 29 1.150 0.192 6.441 0.0821 6.960 0.3130 37 0.990 0.202 5.154 0.0792 5.690 0.3617 44 0.840 0.184 5.896 0.0812 6.932 0.1139 58

dear all, I am a new comer to R and statistic. Now I have a little confuse about the package pls. I have to use 5 components to form a model. There are strong relationship between some of the components, which leads to the changes of the sign of each coeficeince, of course this is unwanted when using the normal regression way. So I choose the way of PLS, which is good at solve this kind of

HI, Dear R community, I am using the following codes to plot, however, the lines code works. But the line was not drawn on the previous plot and did not shown up. How comes? # specify the data for missense simulation x <- seq(0,10, by=1) y <- c(0.952, 0.947, 0.943, 0.941, 0.933, 0.932, 0.939, 0.932, 0.924, 0.918, 0.920) # missense z <- c(0.068, 0.082, 0.080, 0.099, 0.108, 0.107,

Hi, when I generated a survfit() object, I can get number of patients at risk at various time points by using summary(): fit<-survfit(Surv(time,status)~class,data=mtdata) summary(fit) class=1 time n.risk n.event survival std.err lower 95% CI upper 95% CI 9.9 78 1 0.987 0.0127 0.963 1 41.5 77 1 0.974 0.0179 0.940 1 54.0 76

Hello, not understanding the output of prcomp, I reduce the number of components and the output continues to show cumulative 100% of the variance explained, which can't be the case dropping from 8 components to 3. How do i get the output in terms of the cumulative % of the total variance, so when i go from total solution of 8 (8 variables in the data set), to a reduced number of

Hi, When I run the survfit function, I want to get the restricted mean value and the standard error also. I found out using the "print" function to do so, as shown below, print(km.fit,print.rmean=TRUE) Call: survfit(formula = Surv(diff, status) ~ 1, type = "kaplan-meier") records n.max n.start events *rmean *se(rmean) median 200.000

Hello All, Specifying 'type = "response"' when using predict() on a model fit using glm(...,family="binomial") returns fitted probabilities. Is it possible to get the same from a model object fit using glmmPQL() ? Thanks in advance, Rob _____________________________________________________ Rob Keefe Lab: (208) 885-5165 M.S. student

Hello I am new in R. I am trying to implement Biomod 2 package. However, I have a doubt. I want to calculate the mean and sd of "Testing.data" (ROC and TSS) > # let's print the ROC scores of all selected models > myBiomodModelEval_55["ROC","Testing.data",,,] RUN1 RUN2 RUN3 RUN4 RUN5 RUN6 RUN7 RUN8 RUN9 RUN10 0.938 0.938 0.926 0.931 0.939

Dear R-helpers, To get curves for a pseudo cohort other than the one centered at the mean of the covariates, I have been trying to use the newdata argument to survfit with no success. Here is my model statement, the newdata and the ensuing error. What am I doing wrong? > summary(fit) Call: coxph(formula = Surv(Start, Stop, Event, type = "counting") ~ Week + LagAOO + Prior.f +

Dear R users, I'm trying to do betareg on my dataset. Dependent variable is not normally distributed and is proportion (of condom use (0,1)). But I'm having problems: gyl<-betareg(cond ~ alcoh + drug, data=results) Error in optim(par = start, fn = loglikfun, gr = gradfun, method = method, : initial value in 'vmmin' is not finite Why is R returning me error in optim()? What

Hi everyone I'm using Tukey HSD as post-hoc test following a lme analysis. I'm measuring hemicelluloses in different species treated with three different CO2 concentrations (l=low, m=medium, h=high). The whole experiment is a split-plot design and the Tukey-function from the package multcomp is suitable for lme-analysis with random factors. The analysis works fine but I get a non

Hi, Can anybody tell me what the message below means and how to overcome it. Thanks, Neil Warning message: X matrix deemed to be singular; variable 2 in: coxph(Surv(age_at_death, death) ~ project$pluralgp + project$yrborn + ......... >

Dear all,I am a new user of WinBUGS and need your help. After running the following code, I got parameters of beta0 through beta4 (stats, density), but I don't know how to get the prediction of the last value of h, the variable I set to NA and want to model it using the following code.Does anyone can given me a hint? Any advice would be greatly appreciated.Best

Hi, I found a discrepancy between results in R and Stata for a factor analysis with a promax rotation. For Stata: . *rotate, factor(2) promax* (promax rotation) Rotated Factor Loadings Variable | 1 2 Uniqueness -------------+-------------------------------- pfq_amanag~y | -0.17802 0.64161 0.70698 pfq_bwalk_~ø | 0.72569 0.05570

HI, Dear R community, I have used the following codes this morning, but this afternoon, I got the following errors: > x <- seq(0,10, by=1) > y <- c(0.952, 0.947, 0.943, 0.941, 0.933, 0.932, 0.939, 0.932, 0.924, 0.918, 0.920) # missense > z <- c(0.068, 0.082, 0.080, 0.099, 0.108, 0.107, 0.101, 0.105, 0.118, 0.130, 0.132) # missense False Negative > p <- c(0.035, 0.036,

Dear R members, I am new in using frailty models in survival analyses and am getting some contrasting results when I compare the Wald and likelihood ratio tests provided by the r output. I am testing the survivorship of different sunflower interspecific crosses using cytoplasm (Cyt), Pollen and the interaction Cyt*Pollen as fixed effects, and sub-block as a random effect. I stratified

Hello, I am attempting to get the standard deviation in multiple distance bins in my spatial data. It appears as though the 'variog' command in the geoR package will do the trick, as one of the outputs from 'variog' is 'variog$sd', which, according to the manual, is the "standard deviation of the values in each bin". However, when I run this command, the

Hello I would like to transfer some Splus functions in R. But I have a problem first about this assignation in Splus : xnom <- deparse(substitute(x)) I am a bad programmer : I don't understand the R help How to modify these functions ? Thank you very much for your help Here are the four functions and a data test

Ol?, Please keep this in the list, I'm cc-ing r-help at r-project.org. And yes, I am Portuguese but R-Help is a mailing list in the English language. As for your new question, I believe that you should start a new thread. This is completely different from the question on computing mean and sd. Ask a new question. Font "arial" is a Microsoft font and as far as I know is not

Dear All: Could you please tell me how I can draw figure formatted like figure 4.18 of MASS (4th) with the attached data set? Thanks Zhongming Yang --------------------------------- -------------- next part -------------- An embedded and charset-unspecified text was scrubbed... Name: sample.txt Url: https://stat.ethz.ch/pipermail/r-help/attachments/20050316/abfdb85e/sample.txt