search for: pdat

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 -0.2741 #Degrees of Freedom:...

Hello, I'm trying to make a lattice plot (using xyplot()). I have included a "layout=c(3,4)" statement, giving me 12 plots per page and an "as.table=TRUE" statement, directing the way the plots are laid out. I have 18 plots altogether and so 6 of them end up on the second page. Everything looks fine for the first page, but the x-axis labels (e.g. 1993, 1994...) are all

...5, 6, 5.5, 5, 4.5, 4, 3.5, 3, 2.8, 2.2, 2, 1.8, 1.6, 1.4, 1.0) for (i in 1:20) { maxCount = 100 * counts[i] for (j in 1:maxCount){ pmat = rbind( pmat, c(i*0.05-0.001,2) ) } } # Convert the matrix to a data frame and add column names. pDat = data.frame(pmat) colnames(pDat) = c("pValue","nonCent") # Create a factor to enable titles on the two panels. nonCent.f = factor(pDat$nonCent, labels=c("Noncentrality = 0.0", "Noncentrality = 2.0")) # Use the lattice histogram function to draw the his...

Per the Posting Guide, why didn't you post the reproducible R code example? On April 24, 2018 8:22:15 PM PDT, Donald Macnaughton <donmac at matstat.com> wrote: >I'm drawing a paneled histogram using the lattice package. I've >succeeded in >adding minor tick marks to the vertical axis, but I can't get the >desired >number of minor tick marks between the major

I'm drawing a paneled histogram using the lattice package. I've succeeded in adding minor tick marks to the vertical axis, but I can't get the desired number of minor tick marks between the major tick marks. I've attached a self-contained program to illustrate the problem. Thanks for your help, Don Macnaughton Here's my sessionInfo: R version 3.4.3 (2017-11-30) Platform:

...obabilities from 'true' parameter values psim <- function(x){ params <- list(p1 = p1t, p2 = p2t, mu1 = mu1t, mu2 = mu2t, t = x) eval.P1 <- eval(P1, params) eval.P2 <- eval(P2, params) P3 <- 1 - eval.P1 - eval.P2 c(x, matrix(c(eval.P1, eval.P2, P3), ncol = 3)) } pdat <- sapply(tv, psim, simplify = TRUE) Pdat <- as.data.frame(t(pdat)) names(Pdat) <- c("time", "P1", "P2", "P3") # Generate simulated data set from probabilities n = rep(20, length(tv)) p = as.matrix(Pdat[,2:4]) y <- as.data.frame(rmultinomial(n,p)...

Dear all i could not estimate the optima value or range value in unimodal plot in glm please help me out thanking you regard madan _________________________________________________________________ Hotmail® has a new way to see what's up with your friends. orial_WhatsNew1_052009 [[alternative HTML version deleted]]

...e model probabilities from true parameter values psim <- function(x){ params <- list(p1 = p1t, p2 = p2t, mu1 = mu1t, mu2 = mu2t, t = x) eval.P1 <- eval(P1, params) eval.P2 <- eval(P2, params) P3 <- 1 - eval.P1 - eval.P2 c(x, matrix(c(eval.P1, eval.P2, P3), ncol = 3)) } pdat <- sapply(tv, psim, simplify = TRUE) Pdat <- as.data.frame(t(pdat)) names(Pdat) <- c("time", "P1", "P2", "P3") # Generate simulated data set from model probabilities n = rep(20, length(tv)) p = as.matrix(Pdat[,2:4]) y <- as.data.frame(rmultinomia...

Dear List, I have a richness data distributing across 20 N to 20 S latitude. (120 E-140 E longitude). I would like to draw the richness in the north hemisphere and a regression line in the plot (x-axis: latitude, y-axis: richness in the north hemisphere). The above demand is done using plot. Then, south hemisphere richness and regression are required to be generated using the same y-axis above

hi, i am writing my master thesis and i am dealing with 146474 observations (panel data), i have just learned the R so i am a beginner!! i am trying to use the "plm" package and i have a duplication problem; i have written the following commands to read my data and create my model >dsn<-plm.data(ds, c("stno", "year")) ds=name of my data, stno=individual

Hi, everyone, Night. I have three questions about multiple linear regression in R. Q1: y=rnorm(10,mean=5) x1=rnorm(10,mean=2) x2=rnorm(10) lin=lm(y~x1+x2) summary(lin) ## In the summary, 'Residual standard error: 1.017 on 7 degrees of freedom', 1.017 is the estimate of the constance variance? Q2: beta0=lin$coefficients[1] beta1=lin$coefficients[2] beta2=lin$coefficients[3]

Hi all, I try to interpolate a data set in the form: time Erg 0.000000 48.650000 1.500000 56.080000 3.000000 38.330000 4.500000 49.650000 6.000000 61.390000 7.500000 51.250000 9.000000 50.450000 10.500000 55.110000 12.000000 61.120000 18.000000 61.260000 24.000000 62.670000 36.000000 63.670000 48.000000 74.880000 I want to get smoothed splines by using the class gam The first way I tried , was

Hi r-users, I want to use the sn package but I got the following message: > install.packages(repos=NULL,pkgs="c:\\Tinn-R\\sn_0.4-12.zip") Warning: package 'sn' is in use and will not be installed updating HTML package descriptions I did tried to do it a few times but it gives the same message.  ________________________________ From: "r-help-request@r-project.org" <r-help-request@r-project.org> To: r-help@r-project.org Sent: Thursday, May 28, 2009 7:30:06 PM Subject: R-help Di...