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Hello. My name is Akashah. i work at metabolic laboratory. From my study, i found that volcano plot can help a lot in my section.  i already studied about the volcano plot and get the coding to run in R software, unfortunately, there is may be something wrong with the coding. This is because  no graph appear, but no error (blue color text) was shown on the R console. Below is the coding for

# lda.r > # > # Author: Amsha Nahid, Jairus Bowne, Gerard Murray > # Purpose: Perform Linear Discriminant Analysis (LDA) > # > # Input: Data matrix as specified in Data-matrix-format.pdf > # Output: LDA plot > # > # Notes: Missing values (if any) are replaced by the half of the lowest > # value in the entire data matrix. >

hello, i already include the error in blue color word. i hope it can help you to understand my question. if not burden you, please give me a guide how to correct the error or maybe you can correct the coding cause error. thank you. > # lda.r > # > # Author: Amsha Nahid, Jairus Bowne, Gerard Murray > # Purpose: Perform Linear Discriminant Analysis (LDA) > # > #

> # >> # Generate the figures (on screen) >> # >> # Image generation - function definition >> pic_onscr<-function(matrix, title, cex_val=1) > + {x11() + par(mgp=c(5,2,0), # axis margins + # (title, > labels, line) + mar=c(7,4,4,2), # plot margins (b,l,t,r) + > las=1) # horizontal labels + plot(matrix, # data to plot + >

Greetings list, I am new to programming in R, and am using nnet() function for a project on neural networking. Firstly I wish to ask if there is any pdf explaining the algorithm nnet uses, which could tell me what the objects of the nnet class, like 'conn', 'nconn, 'nsunits', n and 'nunits' mean, and how weights are calculated. The package pdf has little or no

Dear R list, I have a recurring problem with the languageR package, specifically the aovlmer.fnc function. When I try to run the following code (from R. H. Baayen's textbook): # Example 1: library(languageR) latinsquare.lmer <- lmer(RT ~ SOA + (1 | Word) + (1 | Subject), data = latinsquare) x <- pvals.fnc(latinsquare.lmer,

Dear R-help: I've been trying to run pvals.fnc in the newest version of R (2.13.0). The function lmer worked fine, but when I tried to use pvals.fnc on the lmer object, I got the following error: "Error in pvals.fnc(elogr.subj.dys.sum.3x3.p, nsim = 10000) : trying to get slot "coefs" from an object (class "summaryDefault") that is not an S4 object." How can I

Hi everybody! I was using the function pvals.fnc from package 'languageR' until April. I do not know which version. Yesterday I updated all my packages and tried to run my loop again. Now I get the following error message: error in pvals.fnc(mm, nsim = 1000) : MCMC sampling is not yet implemented in lme4_0.999375-27 for models with random correlation parameters I guess it?s because of

Hi Everyone, I am using R 2.10.1. lmer function works properly, however pvals.fnc () does not despite the fact that I uploaded: - library(lme4) - library(coda) - library(languageR) This is the error message I get pvals.fnc(lexdec3.lmerE2, nsim=10000)$fixed Error in pvals.fnc(lexdec3.lmerE2, nsim = 10000) : MCMC sampling is not yet implemented in lme4_0.999375 for models with random

Hi. I get an error message about not converging when I try and use the pvals.fnc from the languageR library. The LMER analysis worked fine (See below). I am not an expert so I don't understand why the LMER worked but not the pvals.fnc Any help gratefully received. - Mike AIC BIC logLik MLdeviance REMLdeviance -7324 -7254 3673 -7451 -7346 Random effects: Groups

Hi all, I'm analyzing micro array data.. it has produced a file (to be specific matrix) withdimension of 35556 2. first few lines of the matrix are as below.. probe_name control.fdr.pvals.present 10338001 0.000440001 10338002 0.000583093 10338003 0.000528449 10338004 0.000610362 10338005 0.000151825 10338006 0.0001733 10338007 0.000152924 Now, i want only rows whose

Hola Manuel lo he tratado de hacer pero me sale Error: unexpected string constante in: "anova(a,as,test=Chisq") no tengo ni idea de por qué... Me resulta alucinante no poder contar ya con pvals.fnc. ¿Será imposible hacerse con ello? Saludos, Miguel -------------------------------------------- El vie, 13/6/14, Manuel Azcárate <mazcarategarcia en gmail.com> escribió:

Existe discusión sobre el uso de los p-valores en modelos mixtos. Como se ha dicho antes, para mi lo más adecuado es comparar modelos mediante la función anova. Por Internet se puede encontrar un buen libro de Douglas Bates y en español, busca modelos mixtos con R de Luis Cayuela, enfocado hacia ecología, pero está muy bien El 13/06/2014 14:00, "Jorge I Velez"

Hola a todos, quería preguntaros un medio para obtener los valores p usando lmer. He tratado con pvals.fnc, que es lo que me habían recomendado, pero por algún motivo no está ya disponible etc. Ésta es la función que tengo, pero da las "t", sin los valores p. Aunque Baayen indica que valores por encima de 2 son significativos necesito saber las p. resultado = lmer(rt_ln ~ (fre_ln *

Hi, I have two data frames each with 5 columns and different number of rows. some of the row names in one data frame are the same as the row names in the other. I want to be able to merge the two data frames to get a new data frame in which the duplicated row names are only shown once with the data for the rest of the columns used from the first data frame. Essentially, I want to make a union

Hi, I was trying to evaluate the pearson correlation and the p-values for an nxm matrix, where each row represents a vector. One way to do it would be to iterate through each row, and find its correlation value( and the p-value) with respect to the other rows. Is there some function by which I can use the matrix as input? Ideally, the output would be an nxn matrix, containing the p-values

It is easy to spot response nonlinearity in normal linear models using plot(something.lm). However plot(something.glm) produces artifactual peculiarities since the diagnostic residuals are constrained by the fact that y can only take values 0 or 1. What do R users find most useful in checking the linearity assumption of logistic regression (i.e. log-odds =a+bx)? Patrick Foley patfoley at

Dear all, I'm performing a t-test on two normal distributions with identical mean & standard deviation, and repeating this tests a very large number of times to describe an representative p value distribution in a null case. As a part of this, the program bins these values in 10 evenly distributed bins between 0 and 1 and reports the number of observations in each bin. What I have noticed

Hi, This report deals with p-values coming from chisq.test using the simulate.p=TRUE option. The issue is numerical accuracy and was brought up in previous bug reports 3486 and 3896. The bug was considered fixed but apparently was only mostly fixed. Just the typical problem of two values that are mathematically equal not ending up numerically equivalent. Consider this series of three 2x2

I have the following contingency table dat <- matrix(c(1,506,13714,878702),nr=2) And I want to test if their is an association between events A:{a,not(a)} and B:{b,not(b)} | b | not(b) | --------+-----+--------+ a | 1 | 13714 | --------+-----+--------+ not(a) | 506 | 878702 | --------+-----+--------+ I am worried that prop.test and chisq.test are not valid given the