similar to: question about multinom function (nnet)

Dear R users, I have trouble obtaining the same results for nested Anova with two fixed factors when using lm and aov functions. The formulas are: > e1=aov(y~x/z) > e2=lm(y~x/z) summary(e1) Df Sum Sq Mean Sq F value Pr(>F) x 47 260.0 5.5 18.0088 < 2.2e-16 *** x:z 195 169.6 0.9 2.8318 < 2.2e-16 *** Residuals 14425

Dear R users, I have posted this question several days ago and received not a single suggestion. I believe I have provided sufficient information for at least some help. Here I repost the question with several modifications. I want to run nested fixed-factor Anova in R on different experiments. I have 48 levels of the main factor x1 and 242 levels of the nested factor z1, and continuous response

Dear R users, I want to run nested fixed-factor Anova in R on different experiments. In this toy example I have 3 levels of the main factor x1 and 7 levels of the nested factor z1 x1 and continuous response variable y1. x1 [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 [38] 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 [75] 3 3 3

I inherited a function written either for an older version of R or SPlus to draw a brace, "{", in a graph. It uses par("uin") to determine the scaling of the quarter circles that make up segments of the brace, but that setting doesn't exist in current R. I'm guessing that, in the function below, ux, uy can be defined from par("usr") and

Hello All I have a very long vector of unique predictor values and 6 significant digits setting for the smooth.spline rounds them off. Is there any way of increasing the significant digits withour recompiling a lot if code (simple editing and tham sourcing of "smooth.spline.r" function does not work, probably due to presence of Fortan functional calls)? Thank you very much in advance

Dear all, I need to run a interactive procedure where the user will need click on the screen (over a XY plot) and I need to record the XY coordinate which the user clicked. Roughly I wrote a short code below. You see that I suppose that the user will choose four coordinates inside the region of intersection between three segmentes. On each click, I would like to record the position clicked in a

sox works great. to splice out a 10-minute segment starting 12m34s into a .wav file: sox infile.wav outfile.wav trim 12:34 10:00 to splice two segments together, well: cat seg1.wav seg2.wav > joined.wav <p>samurai.fm wrote: > SOX might work? > > -----Original Message----- > From: owner-icecast@xiph.org [mailto:owner-icecast@xiph.org] On Behalf Of > Mailing List Receiver

Need some assistance, I have a firewall I am trying to reinstall the os, on, and I have no idea how to do it, they sent me syslinux, but I have no idea what kernel to use, or really how to install it using syslinux. Please, any help will be appreciated. Scott Latta Network Administrator Techsupport Supervisor Nexity Bank A+, NET+, MCP 205-298-6482

Hi, Nicolas Indeed, I did not have ant installed and installing it allowed me to overcome the previous error. However the next one appeared. I have ran make with ENABLE_OPTIMIZED=1 VERBOSE=1 and here is the output (the last part of it) make[2]: Entering directory `/home/svozniuk/llvm/vmkit/mmtk/java' /usr/bin/ant -buildfile /home/svozniuk/llvm/vmkit/mmtk/java/build.xml Buildfile:

Hi, I am searching for methods to compare regression models with an ordered categorical response variable (polr versus multinom). The pattern of predictions of both methods (using the same predictor variables) is quite different and the AIC is smaller for the multinom approach. I guess polr has more strict premises for the structure of the response variable, which methods can be used to test for

Best R Help, I like to estimate a Multinomial Logit Model with 10 Classes. The problem is that the number of observations differs a lot over the 10 classes: Class | num. Observations A | 373 B | 631 C | 171 D | 700 E | 87 F | 249 G | 138 H | 133 I | 162 J | 407 Total: 3051 Where my data looks like: x1 x2 x3 x4 Class 1 1,02 2 1 A 2 7,2 1 5 B 3 4,2 1 4 H 1 4,1 1 8 F 2 2,4 3 7 D 1 1,2 0 4 J 2 0,9

I want to get the logLik to calculate McFadden.R2 ,ML.R2 and Cragg.Uhler.R2, but the value from multinom does not have logLik.So my quetion is : is logLik meaningful to multinomial logistic model from multinom?If it does, how can I get it? Thank you! ps: I konw VGAM has function to get the multinomial logistic model with logLik, but I prefer use the function from "official" R

Is anyone aware of a way to check whether multinom has converged by checking a component of the output ? I'm not familar with nnet but, since multinom calls nnet , maybe there is an extra argument once can send to multinom to capture this information. Thanks.

Dear R users, I'm using a multinomial LOGIT model to analyse choice behaviour of consumers (as part of my masters thesis research). Using the R documentation and search on the R website I have a working script now. Parameters are estimated and I can access them via coefficients(multinom.out). In order to see if the parameters are significant I like to access the standard errors in the

Dear all, I'm fitting a multinom function to my dataset (multinom(outcome~age+K+D)) and I need to present my results on a poster. Does someone know a nice way of doing that? I think I saw in an archive that you cannot plot a multinom.object, is it true? Thank you by advance for your help, Cheers Camille

Hi, I am trying to specify a multinomial logit model using the multinom function from the nnet package. Now I add another independent variable and it halves the AIC as given by summary(multinom()). But when I call Anova(multinom()) from the car package, it tells me that this added variable is insignificant (Pr(>Chisq)=0.39). Thus, the improved AIC suggests to keep the variable but the Anova

Hi all, I'm working on a multinomial (or "polytomous") logistic regression using R and have made great progress using multinom() from the nnet library. My response variable has three categories, and there are two different possible predictors. I'd like to use the likelihoods of certain models (ie, saturated, fitteds, and null) to calculate Nagelkerke R-squared values for

Dear All: I am interested in multinomial logit models (function multinon, library nnet) but I'm having troubles in choose whether to define the predictors as factors or not. I had posted earlier this example (thanks for the reply ronggui): worms<- data.frame(year= rep(2000:2004, c(3,3,3,3,3)),age=rep(1:3,5),

I have RedHat linux 9 with R 1.8. I'm estimating models with multinom with a dependent variable that has 3 different values. Sometimes the models run fine and I can understand the results. Sometimes when I put in another variable, I see an indication that the estimation did work, but then I can't get the summary method to work. It's like this: > votemn1 <-

Dear R users, The nnet package includes the multinom method for the confint function. The R Help file (?confint) for the generic function in the stats package and the help files for the glm and nls methods in the MASS package indicate that one can use the "parm" argument as "a specification of which parameters are to be given confidence intervals, either a vector of numbers or