similar to: Keywords and Concepts - CTFS package

Hi again; I have placed many examples in the CTFS Rd pages because my audience really really likes lots of examples in order to understand the options available in a functions. At this time I have set them all to \dontrun{}. however, this isn't because the example command line with its function and options won't work, but rather that CTFS specific datasets must exist to have the

I am wondering if there is an R function that could estimate a generalized nonlinear mixed model. >From my reading it seems that nlme from the nlme package can fit nonlinear mixed models, while lmer from the lme4 package can fit generalized linear mixed models. One alternative I?ve found is gnlmix from the repeated package, although this only allows for a single random effect. Is there

I have tried and tried unsuccessfully to place a legend outside the plot frame of a graph. This would allow me to draw a legend for an image() plot. But any legend I add is cut off outside the axes. Is there a way of doing this? Thanks for any advice on how to make this work (I'm using R1.5.1 with Windows 2000). Richard Condit Smithsonian Tropical Research Institute Unit 0948 APO AA

I've been given the job of extracting some data from the United States 2000 census (files at http://www2.census.gov/census_2000/datasets/Summary_File_2/Maryland/all_ Maryland.zip 52M). I'm only interested in Census Block Groups (CBGs) located within Baltimore City, Maryland. Additionally, I just have to extract certain data fields. I think I'll be using Summary File 2. This is my first

Dear fellows, I'm trying to extract the AIC statistic from a GLM model with quasipoisson link. The formula I'm referring to is AIC = -2(maximum loglik) + 2df * phi with phi the overdispersion parameter, as reported in: Peng et al., Model choice in time series studies os air pollution and mortality. J R Stat Soc A, 2006; 162: pag 190. Unfortunately, the function logLik

Hello all, I am hoping to use survival analysis to examine whether parasite attack increases nest death in a species of social wasp. I therefore have data for 1. Whether the nest "died" in the 6 week census period ("Status", where 1=died, 0=survived) 2. The day number of death/last recorded day it was observed alive. 3. Whether the nest was attacked by the parasite (0/1 as

Hola, El problema está con el nombre de las columnas y las filas del fichero que importas. Mira este detalle tras hacer la importación: > names(mort) [1] "X" "X15.24..79." "X25.34..79." [4] "X35.44..79." "X45.54..79." "X55.64..79." [7] "X65.74..79." "X75.84..79."

Hola. Como te dijo Carlos, el problema está en los nombres de las columnas y en los nombres de las filas. Cuando hice la importación (con dd<-read.csv('mortality.csv'), tuve problemas con las filas de nombre: - Malignant tumour of the larynx trachea bronchus and lungs - Malignant tumour of the lip pharynx and mouth - Other endocrinological metabolic and nutritional conditions

I have been trying the integrate function in R, a function which would be very useful for a current project of mine. But I am encountering errors integrating the one function I have tried. The function to be integrated is a product of a gamma demsity and a normal density: gamma.by.normal_function(y,x,shape,scale,stdev) return( dgamma(y,shape=shape,scale=scale)*

Hello R Community, I have the following design question. I have a data set that looks like this (shortened for the sake of example). Gender Age M 70 F 65 M 70 Each row represents a person with an age/gender combination. We could put this data into a data frame. Now, I would like to do some actuarial analysis on this data set. To do so, I need to create and store

[New to the community; still in early part of R's learning curve.] Several months ago, I was requested to generate some graphs on a periodic basis. Accordingly, I managed to figure out a way to do so, using a combination of Perl and R (in a FreeBSD environment). While I've needed to adjust a few things here and there, the general approach has been pretty solid , and the R part has had

i am trying to replicate the following graph using xyplot : attach(x) plot ( jitter(type), mortality, pch=16, xlim = c(0.25, 3.75)) lines ( c(1-0.375,1.375) , c ( median(mortality[type==1]), median(mortality[type==1])), lwd=5,col=2) lines ( c(2-0.375,2.375) , c ( median(mortality[type==2]), median(mortality[type==2])), lwd=5,col=2) lines ( c(3-0.375,3.375) , c ( median(mortality[type==3]),

Hello, all. I have co-opted a number of functions that can be used to plot the hazard/survival functions and associated density distribution for a Gompertz mortality model, given known parameters. The Gompertz hazard model has been shown to fit relatively well to the human adult lifespan. For example, if I wanted to plot the hazard (i.e., mortality) functions: pop1 <- function (t) {

Dear all, I'm trying reproduce an example of bioassays Yielding Concentration-Mortality Data particularly control - adjustment model from book Bioassay of Entomopathogenic Microbes and Nematodes chapter 7 with R. I used glm with family=binomial and link=probit, but I do not know how to implement parameter gamma (control mortality - mortality of the untreated control insect in this exaple)

Estimados Queremos con el paquete FactoMineR hacer este tipo de tabla de mortalidad que lea los datos desde de una tabla csv Realizamos lo que viene en la ayuda y es muy interesante, sin embargo cuando mandamos a leer desde la tabla csv original de los autores no hace el análisis porque algo falta y no nos percatamos de que es. Adjunto tabla original Saludos cordiales #ESTO ES LO QUE

Dear All, I've tried to sum columns -- different species of flowers, fruits plus twigs -- with NAs to get litterfall/trap, and then after use litterfall to calculate production (litterfall (grams)/ hectare/ day. But R 'sees' litterfall/trap as a string. My question: How to use basic mathematical functions to deal with NAs in data management. Example (as you can note I have many

Hello everybody, I have an Ascii-grid (100x100m) with population density over Switzerland (local coordinations system, CH LV03). Now I would like to have a nice graphic to present the data. I would like to make a plot that will show the density as the z-variable and raise for example a stacking pillar showing how high the density is in that hectare. I attached a map that's similar to what I

Hello, I want to create side-by-side maps of similar attribute data in two different cities using a single legend. To simply display side-by-side census block group boundary (non-thematic) maps for Minneapolis & Cleveland I do the following: library(rgdal) library(sp) Minneapolis=readOGR("../Minneapolis/Census/2010/Census_BlockGroup_GEO/","tl_2010_27053_bg10")

Hi I am trying to carry out some maximum likelihood estimation and I'm not making much headway, and I'm hoping that someone will be able to point me in the right direction. I am modelling mortality statistics. One way to do this is to model the mortality rate (or, more accurately, log of the mortality rate, log_m) as (say) a constant plus a proportion of age, plus time, so: r_1 <-

Hi all, I am not sure how to handle interactions with categorical predictors in the GAM models. For example what is the different between these bellow two models. Tests are indicating that they are different but their predictions are essentially the same. Thanks a bunch, > gam.1 <- gam(mortality.under.2~ maternal_age_c+ I(maternal_age_c^2)+ + s(birth_year,by=wealth) + +