similar to: factor labels in model.frame

Kevin Wright wrote: > library(nlme) > m2 <- gnls(conc ~ t1*(1-t2*exp(-k*time)), > data = df.Chloride, > start = list( > t1 = 35, > t2 = 0.91, > k = 0.22)) So my error was to use nls instead that gnls. Thanks a lot, Kevin. > summary(m2) > plot(m2) > lag.plot(resid(m2), do.lines=FALSE) >

I would like to perform partial mantel tests on only within group values, with "between group" values assigned to NA. This is possible in package ncf partial.mantel.test, however this sues a different permutation to that used in ecodist.ecodist will not accept data with NA values, returning a "matrix is not square error. is it possible to perform this test in ecodist? many thanks

Hi, I have a data-matrix: > PID sato hrs fim health 214 3 4.376430 6.582958 5 193 6 4.361825 3.138525 6 8441 6 4.205771 3.835886 7 7525 6 4.284489 3.245139 6 6806 7 4.168926 2.821833 7 5682 7 1.788707 1.212653 7 5225 6 1.651463 1.436980 7 4845 6 1.692710 1.267359 4 4552 5 1.686448 1.220539 6

Hi all, I have a matrix simulating migration in a spatial model. I want to be able to define movement (the values of m1, m2 and m3) as only != 0 between adjacent patches and contingent on certain conditions as defined in the function. Here is the code: WET<-function(t) {everglades$precipitation[t]} #simply reads precipitation data from a csv, value is numeric AB<-function(WET,t)

Dear All, I am new for R and SEM. I try to fit the model with Y (ordinal outcome), X (4 categorical data), M1-M3 (continuous), and 2 covariates (Age&sex) as a diagram. library(polycor) model.ly <-specify.model() 1: x -> m1, gam11, NA 2: x -> m2, gam12, NA 3: x -> m3, gam13, NA 4: age -> m1, gam14, NA 5: age -> m2, gam15, NA 6: age -> m3, gam16, NA 7: sex -> m1,

Hi I have a small ISDN PABX , (BRI) at home - Siemens Gigaset 4175 which has cordless DECT extensions. I have set up asterisk on FC3 with two HFC cards and I am using the latest bristuff. I am trying to use * between my ISDN line and my PABX. One card is in TE mode and can receive and make calls OK. I can make and receive external calls to a SIP phone. I cannot get the other card to talk to my

For a pedagogical purpose, I was trying to show how the formula for a simple regression line (~1+x) could be crossed with a factor (~1:group + x:group) to fit separate regressions by group. For example: set.seed(201108) dat <- data.frame(x=1:15, y=1:15+rnorm(15), group = sample(c('A','B'), size=15, replace=TRUE)) m1 <- lm(y~ 1 + x, data=dat)

> On Jun 6, 2017, at 4:01 AM, Jim Lemon <drjimlemon at gmail.com> wrote: > > Hi Bogdan, > Kinda messy, but: > > N <- data.frame(N=c("n1","n2","n3","n4")) > M <- data.frame(M=c("m1","m2","m3","m4","m5")) > C <-

Saludos, tengo un problema que no puedo resolver dentro del R Estoy creando una funcion que a partir de un objeto compuesto por diferentes matrices como el que esta a continuacion: [[1]] M1 M2 M3 M4 sp1 2 0 1 8 sp2 4 5 2 4 sp3 0 0 4 0 sp4 5 7 5 0 sp5 0 4 0 0 [[2]] M3 M2 M4 M1 sp1 1 0 8 2 sp2 2 5 4 4 sp3 4 0 0 0 sp4 5 7 0 5 sp5 0 4 0 0 [[3]]

Any ideas? Sangoma support is closed for the evening. I have the latest Sangoma drivers and Asterisk 1.4 everything installed. When I fire up asterisk, I keep getting "Primary D-Channel on span 1 up" repeated over and over. The B channels never come up. There are no errors in any of the logs, zttool, or the wanpipe tools. Intense pri debug output: < Unnumbered frame: < SAPI:

Thank you David. Using xtabs operation simplifies the code very much, many thanks ;) On Tue, Jun 6, 2017 at 7:44 AM, David Winsemius <dwinsemius at comcast.net> wrote: > > > On Jun 6, 2017, at 4:01 AM, Jim Lemon <drjimlemon at gmail.com> wrote: > > > > Hi Bogdan, > > Kinda messy, but: > > > > N <-

Hello, My name is Ick Hoon Jin and I am Ph. D. student in Texas A & M Univ.. When I run the C embedded in R in the Linux system, I confront the following error after 6,000 iteration. By googling I found this error is from the problem in C. *** caught segfault *** address (nil), cause 'memory not mapped' My C code is following:

I have a big database which more classes in class variable. I want to make each class to one dataset, for example: x1 x2 x3 x4 class a b a c c M1 c b b c c M4 c c a c c M2 c a c a a M2 c c a a a M1 c a b c a M3 c c a b c M3 c a c a b M2 c c a b a M1 How can I make, like: x1 x2 x3 x4 class a b a c c M1 c c a a a M1 c

Dear Contributors I have a problem with the collection of data from the results of a test. I need to perform a comparative test over groups of data , recall the value of the pvalue and create a table. My problem is in the way to replicate the analysis over and over again over subsets of data according to a condition. I have this database, called y: gg t1 t2 d 40 1 1

I have a question regarding significance testing for the difference in the ratio of means. The data consists of a control and a test group, each with and without treatment. I am interested in testing if the treatment has a significantly different effect (say, in terms of fold-activation) on the test group compared to the control. The form of the data with arbitrary n and not assuming equal

Here's another approach: N <- data.frame(N=c("n1","n2","n3","n4")) M <- data.frame(M=c("m1","m2","m3","m4","m5")) C <- data.frame(n=c("n1","n2","n3"), m=c("m1","m1","m3"), I=c(100,300,400)) # Rebuild the factors using M and N C$m <-

Simple matrix indexing suffices without any fancier functionality. ## First convert M and N to character vectors -- which they should have been in the first place! M <- sort(as.character(M[,1])) N <- sort(as.character(N[,1])) ## This could be a one-liner, but I'll split it up for clarity. res <-matrix(NA, length(M),length(N),dimnames = list(M,N)) res[as.matrix(C[,2:1])] <-

I have a 32000 x 14 matrix (M) where entry (x, y) corresponds to person x at a discrete time y. I then have a matrix (M2) of 60000 x 2 where each entry is a an event by a person that is in the above 32000 and at a time that is in the range of the discrete time points above. I want to populate the another matrix (M3) such that (x, y) is the number of events of person x between times y-1 and y. This

first, apologies for so many posts yesterday and today. I am wrestling with nls() and nls2(). I have tried to whittle it down to a simple example that still has my problem, yet can be cut-and-pasted into R. here it is: library(nls2) options(digits=12); y= c(0.4334,0.3200,0.5848,0.6214,0.3890,0.5233,0.4753,0.2104,0.3240,0.2827,0.3847,0.5571,0.5432,0.1326,0.3481) x=

I have several linear models on the same data: m1 <- lm(y ~ poly(x,1)) m2 <- lm(y ~ poly(x,2)) m3 <- lm(y ~ poly(x,3)) What I don't understand is why anova(m1, m2, m3, test="F") - yields the same RSS and SS values, but a different p-value from anova(m1, m2, test="F") - when it also yields the SAME as anova(m2, m3, test="F") What am I missing? Rob