similar to: On p-values presented in the summary of Linear Models

Hi, Is it possible to place the group number in a cluster? The best example I found was at https://www.crops.org/images/publications/cs/42/5/1584f4.jpeg (see I, II, IIIa, IIIb) It would help to identify the group given by cutree since branches can turn around and they necessarily are not plotted in order (group 2 is not necessarily the second from the left). Thanks for any help. All the

Hi, I'd like to find which values of x will give me a y. In other words, in the example of a gaussian curve, I want to find the values of x that will give me a density, let's say, of 0.02. curve(((1/(sqrt(2*pi)*10))*exp(-((x-50)^2)/(2*10^2))),xlim=c(0,100)) Thanks for any help, Antonio Olinto ------------------------------------------------- WebMail Bignet - O seu provedor do

Thanks for your reply Nassar. What I really want is to overlay (like add=TRUE) the plots 1 and 2. With plots "at the same screen" I meant overlaid and not one beside the other, i.e., only one plot with all the points (1 to 10) in blue (or any other color), the points 5 to 9 in red and a regression line from points 5 to 9. Best regards, Antonio Olinto ----- Original Message -----

Dear R-list members, Some months ago I wrote a message on the usage of gnls (nlme library) and here I come again. Let me give an example: I have a 10 year length-at-age data set of 10 fishes (see growth.dat at the end of this message) and I want to fit a von Bertalanffy growth model, Li= Linf*(1-exp(-k*(ti-t0))) where Li = length at age i, Linf= asymptotic length, k= curvature parameter, ti=

Dear list members I want to analyze separately the months of a time series. In other words, I want to plot and fit models for each month separately. Taking the example of http://a-little-book-of-r-for-time-series.readthedocs.org/en/latest/src/timeseries.html births <- scan("http://robjhyndman.com/tsdldata/data/nybirths.dat") birthstimeseries <- ts(births, frequency=12,

Dear R-List members, I want to check if a set of measurements follows better a gamma or a lognormal distribution (see data below). Using shapiro.test I can test for normality (shapiro.test(log (Lt)). To test for gamma (and normal) distribution I would use ks.test but I need to specify its shape and scale. How should I calculate these values in R? I tried > Lt.fit <- glm(Lt ~ 1,

Hello I'm translating a Visual Basic routine to R. Which command in R is similar to "select case" in VB? See the example: select case int(AG) case 0, 5, 8, 10 VAR = 37 case 1, 4 VAR = 70 case 3, 6, 9 VAR = 90 case 2, 7 VAR = 112 end select A chain of "if else" would not be very elegant. Is there another option? Thanks in advance. Best regards. Antonio

Dear R-list members Here goes a question on data frames: I want to create a new data frame excluding some records (rows) from an existing one. Considering the data frame "fish.dat" at the end of this message, I can make a boxplot(Ring~Radius) and identify the points at rows 11 and 25 as outliers. With the command fish.dat[c(11, 25),] I can identify which fishes are related to

Hi, Some time ago I asked about how to use comma as decimal separator in plots and Mr. Paul Murrell wrote: ------- You could try something with axis() and chartr(), like ... par(mfrow=c(2,1)) plot(1:10/11, rep(1, 10), main="Standard X-Axis") plot(1:10/11, rep(1, 10), main="Customised X-Axis", axes=F) axis(1, at=pretty(1:10/11),

Dear R-list members, Cynthia M. Jones wrote a paper (Fitting growth curves to retrospective size-at-age data, Fisheries Research 46(2000):123-129; abstract at http://www.elsevier.nl/gej-ng/10/19/44/70/24/37/abstract.html)where the SAS procedure MIXED, Macro NLINMIX (Littell et. al., 1996)was used to estimate the von Bertalanffy growth function parameters assuming that data from the same fish are

Hi to all, So I'm also a new user. I downloaded the program last week and I think it's great. Thanks to those who have developed R. I have a special interest in GLM as a tool to describe fisheries and its variables and I'm just begging to study it. As I could understand there's two types of GLM sun of squares: in "type I" the factors are added in sequence and

Hello R-list members, I’m trying to make a min-avg-max plot (like a boxplot, without box and outliers, i.e., for each class of "x" a vertical line indicating the range (max-min) and an horizontal line or point indicating the mean) with data like: Year Avg Min Max 98 10 7 13 99 12 10 15 01 11 6 14 Which command should be used? Many thanks, Antonio Olinto

Dear R users, I d like to assess the effect of "treatment" covariate on a disease relapse risk with the package cmprsk. However, the effect of this covariate on survival is time-dependent (assessed with cox.zph): no significant effect during the first year of follow-up, then after 1 year a favorable effect is observed on survival (step function might be the correct way to say that ?).

Hi, There is something I don't get with object of class "mle" returned by a function I wrote. More precisely it's about the behaviour of method "confint" and "profile" applied to these object. I've written a short function (see below) whose arguments are: 1) A univariate sample (arising from a gamma, log-normal or whatever). 2) A character string

Dear R Helpers, I have noticed that when I use lmer to analyse data, the summary function gives different values for the AIC, BIC and log-likelihood compared with the anova function. Here is a sample program #make some data set.seed(1); datx=data.frame(array(runif(720),c(240,3),dimnames=list(NULL,c('x1','x2','y' )))) id=rep(1:120,2); datx=cbind(id,datx) #give x1 a

Hi, I am trying to do logistic regression for data of 104 patients, which have one outcome (yes or no) and 15 variables (9 categorical factors [yes or no] and 6 continuous variables). Number of yes outcome is 25. Twenty-five events and 15 variables mean events per variable is much less than 10. Therefore, I tried to analyze the data with penalized regression method. I would like please some of the

Dear List, I used rlm to calculate two regression models for two data sets (rlm due to two outlying values in one of the data sets). Now I want to compare the two regression slopes. I came across some R-code of Spencer Graves in reply to a similar problem: http://www.mail-archive.com/r-help at stat.math.ethz.ch/msg06666.html The code was: > df1 <- data.frame(x=1:10, y=1:10+rnorm(10))

I'm attempting to do model selection with AIC, using a glm and a lognormal distribution, but: fit1<-glm(BA~Year,data=pdat.sp1.65.04, family=gaussian(link="log")) ## gives the same result as either of the following: fit1<-glm(BA~Year,data=pdat.sp1.65.04, family=gaussian) fit1<-lm(BA~Year,data=pdat.sp1.65.04) fit1 #Coefficients: #(Intercept) Year2004 # -1.6341

As to call files of another softwares(as, Excel, minitab) to be manipulated inside of R-plus? Respectfully Regiane -------------- next part -------------- An HTML attachment was scrubbed... URL: https://stat.ethz.ch/pipermail/r-help/attachments/20011112/23b21666/attachment.html

Hi, I want to do a global likelihood ratio test for the proportional odds logistic regression model and am unsure how to go about it. I am using the polr() function in library(MASS). 1. Is the p-value from the likelihood ratio test obtained by anova(fit1,fit2), where fit1 is the polr model with only the intercept and fit2 is the full polr model (refer to example below)? So in the case of the