Displaying 20 results from an estimated 4000 matches similar to: "as.integer and indexes error"
2004 Aug 05
1
cross random effects (more information abuot the data)
Dear friends,
I have asked last few days about cross-random effects
using PQL, but I have not receive any answer because
might my question was not clear.
My question was about analysing the salamander mating
data using PQL. This data contain cross-random effects
for (male) and for (female). By opining MASS and lme
library. I wrote this code
sala.glmm <- glmmPQL(fixed=y~WSf*WSM,
2013 Mar 13
3
Assign the number to each group of multiple rows
Dear R users,
My data have repeating "beh" parameter : 1 or 2 - type of animal behavior
in subsequent locations. I need to assign unique number to each sequence of
locations.
My data is:
>data=data.frame(row=seq(1:10),beh=c(1,1,1,2,2,2,1,1,2,2))
>attach(data)
>data
row beh
1 1 1
2 2 1
3 3 1
4 4 2
5 5 2
6 6 2
7 7 1
8
2018 Jan 09
3
barplot_add=TRUE
Dear R users
aim
Barplot of insect trap catches (y variable trapcatch) at one specific station (variable FiBL_Hecke) from week 1-52 ( x variable week).
It works well using the function tapply (sum trapcatch per week, males and females not separated), however, I intend to separate the y variable trapcatch in males and females (variable m_w: m and w)
problem
I used the function "add" to
2011 Feb 15
1
quick question about binary data
Dear all,This is both an R and a statistics question. I want to test whether males and females of a given species tend to co-occur in a given sampling unit more frequently than expected by chance. I'm thinking about using a binomial distribution with p as the sex ratio of the entire population. So, even though the population sex ratio is close to 50:50, each sampling unit would have
2008 Feb 06
1
Nested ANOVA models in R
Hi,
I'm trying to work through a Nested ANOVA for the following scenario:
20 males were used to fertilize eggs of 4 females per male, so that
female is nested within male (80 females used total). Spine length
was measured on 11 offspring per family, resulting in 880
measurements on 80 families.
I used the following two commands:
summary(aov(Spinelength ~ Male*Female))
and
2012 Nov 05
1
Post hoc tests in gam (mgcv)
Hi.
I'm analysing some fish biological traits with a gam in mgcv. After several
tries, I got this model
log(tle) = sexcolor + s(doy, bs = "cc", by = sexcolor) +log(tl)
sexcolor is a factor with 4 levels
doy is "day of year", which is modeled as a smoother
tl is "total length of the fish"
The summary of this models is (only parametric coefficientes):
Parametric
2005 Mar 22
1
List of tables rather than an extra dimension in the table or (l)apply(xtabs)
I'm not sure how to best explain what I am after but here goes. I have a data frame with 2 geographical factors. One is the major region the other is the component regions.
I am trying to process all the regions at the same time without using "for". So I need (think, I do) a list of matrices each structured according to the number of subregions within each region.
So is there a
2012 Oct 05
1
Error in lmer: asMethod(object) : matrix is not symmetric [1, 2]
Dear R Users,
I am having trouble with lmer. I am looking at recombinant versus non
recombinant individuals. In the response variable recombinant
individuals are coded as 1's and non-recombinant as 0's. I built a model
with 2 fixed factors and 1 random effect. Sex (males/females) is the
first fixed effect and sexual genotype (XY, YY, WX and WY) the second
one. Sexual Genotype is
2018 Jan 09
0
barplot_add=TRUE
Hi, Sibylle,
since you write '"mathematically" add', does
barplot(rbind(m$trapcatch, w$trapcatch))
do what you want (modulo layout details)?
Hth -- Gerrit
---------------------------------------------------------------------
Dr. Gerrit Eichner Mathematical Institute, Room 212
gerrit.eichner at math.uni-giessen.de Justus-Liebig-University Giessen
Tel:
2006 Jul 18
1
Classification error rate increased by bagging - any ideas?
Hi,
I'm analysing some anthropometric data on fifty odd skull bases. We know the
gender of each skull, and we are trying to develop a predictor to identify
the
sex of unknown skulls.
Rpart with cross-validation produces two models - one of which predicts
gender
for Males well, and Females poorly, and the other does the opposite (Females
well, and Males poorly). In both cases the error
2011 Mar 10
3
Fw: random sampling steps in R with replacement
Please note is with replacement
From: taby gathoni <tabieg@yahoo.com>
To: R help <r-help@r-project.org>
Sent: Thursday, March 10, 2011 11:53 AM
Subject: [R] random sampling steps in R
Dear all,
Could someone assist me in random sampling steps/code in R? I have a main sample of 42 males and 165 females and I want to come up with about 1000 samples of 20 males and 20 females from
2010 Oct 07
2
first post and bootstarpping problems
Hello to all R users,
I use R for a year now and am dealing with geometric morphometrics of deer skulls. Yes, I am a biologist and my math skills are just beginning to brush up. To cut to the chase...
I have two groups in my data (males and females) and my data is in a simple vector form. Now I need a bootstrap test for this value
szc1 <- ((mean(maleCent)-mean(femaCent))^
2004 May 16
1
Newbie Poisson regression question
Greetings.
I'm getting started learning R, and I'm trying to reproduce some models
I've done previously in SAS. I'm trying to fit simple Poisson
regressions, and I keep getting impossible results: the models predict
negative numbers of cases for many observations. The code for the
models are:
Female.model <- glm(Observed ~ Black + Other, family =
poisson(link=log),
2011 Apr 15
1
GLM and normality of predictors
Hi,
I have found quite a few posts on normality checking of response variables, but I am still in doubt about that. As it is easy to understand I'm not a statistician so be patient please.
I want to estimate the possible effects of some predictors on my response variable that is nº of males and nº of females (cbind(males,females)), so, it would be:
2010 May 16
2
sample
Hi,
I am sampling two random columns from females and two random columns
from males to produce tetraploid offspring. For every female I am
sampling a random male.
In the end I want to write out a a matrix with all the offspring, but
that does not work. I get always only the offspring from the last
females. There must be a mistake in my script:
moms<-read.delim("females.txt",
2010 Dec 09
3
hi have a question about merging.
this is the problem:
load this R data frame over the internet and save it to your hard drive.
http://rss.acs.unt.edu/Rdoc/library/twang/data/raceproling.RData
please show how to save a dataset of males only (the variable male=1) to a new dataframe. Then do the same thing for females (male=0). Then show how to recombine the two datasets to belike the original one except that the female
2006 Jul 03
1
panel ordering in nlme and augPred plots
Hi,
I'm new at this, I'm very confused, and I think I'm missing something
important here. In our pet example we have this:
> fm <- lme(Orthodont)
> plot(Orthodont)
> plot(augPred(fm, level = 0:1))
which gives us a trellis plot with the females above the males,
starting with "F03", "F04", "F11", "F06", etc. I thought the point of
2018 Jan 09
1
barplot_add=TRUE
Dear Gerrit
Thanks a lot. "rbind" seems to be the right function. Unfortunately there is a shift in the x-axis (see pdf). There are 52 trapcatch values each, m and w, but m$trapcatch and w$trapcatch are shifted up to x-value 60.
The follow-up lines for temp and humidity are fine.
Thanks
Sibylle
setwd("~/Desktop/DatenLogger2017") # am Mac sks
trap =
2018 May 25
2
TukeyHSD for multiple response
Dear all,
I'm testing the effect of species and sex in my sample by using the principal component scores of a PCA analysis.
I have 30 PCs and I tried to see if there is any significant difference from males to females, given that there is a significant effect of phylogeny (factor with several species).
I didi it like this:
Y<-PCA$pc.scores[,1:30]
fit <- manova(Y ~ sp*sex)
2008 May 02
1
Cant resolve Error Message
Hi,
Im having trouble creating the following graph. Here is my code:
library(plotrix)
library(prettyR)
female_improvement
<-read.table("C://project/graphs/gender/breakdown/gender-improvement/female-improvement.csv",
sep=",", header=TRUE)
barp(rbind(rep(length(female_improvement$gender),2),freq(female_improvement$reason)[[1]]),
ylab="22 Males participated in the