similar to: warning in summary(aov())

Hi R-listers, I am trying to compare sections of the beach separated from the HTL to the Veg (east to west), separated into indices (-5 to 30m), HTLIndex. Cross parallel (north to south) are major beach sections (Rayos 1, 2, 3, 4 and MNB). I am thinking to do an ANOVA for each independent rectangle of beach (not exactly but will be treated as). The HTL from (0-5m) in Rayo 1 is one rectangle of

Hi R-listers, I am trying to make a trellis boxplot with the HSuccess (y-axis) in each Rayos (beach sections) (x-axis), for each Aeventexhumed (A, B, C) - nesting event. I am not able to do so and keep receiving: Error in eval(expr, envir, enclos) : object 'Rayos' not found Please advise, Jean require(plyr) resp <- read.csv("ABC Arribada R File Dec 12 Jean

I am wondering if anyone can tell me what the error I'm receiving means below. I thought it said that Aeventexhumed should be converted to a factor, so I tried to do so and received the following error. Please advise. J --------------------------------------------------------- > data.to.analyze.glm <- glm(cbind(MaxHatch, TotalEggs-MaxHatch) ~ > Aeventexhumed, family=binomial,

Hi All, I am wondering if anyone can tell me what the warning message below the model means? J add1(DTA.glm,~ Aeventexhumed + Veg + Berm + HTL + Estuary + Rayos) Single term additions Model: cbind(MaxHatch, TotalEggs - MaxHatch) ~ Aeventexhumed + Veg + Berm + HTL Df Deviance AIC <none> 488.86 4232.9 Estuary 1 454.96 4201.0 Rayos 3 258.80 4008.9 Warning

Hi R-listers, I am wondering if the function aov() in plyr is appropriate for two different types of tests: 1) > summary(aov(EDI ~ VegIndex, data=data.to.analyze)) AND 2) > summary(aov(HSuccess ~ VegIndex + Aeventexhumed + VegIndex:Aeventexhumed, data=data.to.analyze)) the later inclusive of an interaction of the two explanatory variables. This is for obtaining P value and F

Hi R Listers, I am trying to upload a data file and I received this message. It seems that I am still able to make graphs and Aeventexhumed still works in the analysis. Can I ignore this message or do I need to do something about this? Jean > require(plyr) Loading required package: plyr > turtlehatch <- read.csv(file.choose()) > attach(turtlehatch) The following object(s) are

Hi R-listers, I have developed 47 GLM models with different combinations of interactions from 1 variable to 5 variables. I have manually made each model separately and put them into individual tables (organized by the number of variables) showing the AIC score. I want to compare all of these models. 1) What is the best way to compare various models with unique combinations and different number

Hi R - listers, I am receiving an error. Does anyone know what this means? J ggplot(subset(foo, Rayos != "Rayos.NA"), aes(x=HTL, y=DevelopIndex, colour=TotalEggs)) +geom_point() +geom_jitter() + facet_grid(Aeventexhumed ~ Rayos) + geom_smooth(method="lm", fill=NA) + ylim(c(0, 7)) Error in +geom_smooth(method = "lm", fill = NA) : invalid argument to unary

Hi R-listers, Q1) What is the difference between the scatterplot and plot function? Q2) I am able to make a graph with the scatterplot function: scatterplot(DevelopIndex ~ Veg, + data = Turtle, + xlab = "Vegetation border (m)", + ylab = "Embryonic development index") And have been successful. But I do not know if the lines are for:

Hi R-listers, I am using the package plyr. I am just trying to get the hatching success mean of each nesting event and have typed in the following and received the below results: > tapply(HSuccess, Aeventexhumed, mean) A B C 0.2156265 0.1288559 NaN What can I do about NaN? I should be able to get a result for event C because I was able to

After looking at 48 glm binomial models I decided to try the quasibinomial with the top model 25 (lowest AIC). To try to account for overdispersion (residual deviance 2679.7/68 d.f.) After doing so the dispersion factor is the same for the quasibinomial and less sectors of the beach were significant by p-value. While the p-values in the binomial were more significant for each section of the

I am trying to create a frequency distribution and I am a bit confused. Here are the commands I have entered: > data <- read.csv(file="40609_sortedfinal.csv",head=TRUE,sep=",") > NumberOfActionsByStatus = data$STATUS > NumberOfActionsByUser = data$ETS_LOGIN > NumberOfBidOffer = data$BID_OFFER > NumberOfActionsByUser.freq = table(NumberOfActionsByUser) >

Hi The short version of my questions is this: How can I run a chi-square test over a matrix (table) to get the distanaces between rows and then run a SingleLinkage (or other fusion algorithm over the resulting table? ------------ The long-version of my question: My data consists of different data of different countries so I have stuff like how many people can read, write in X,Y,Z countries

Hi, why my script iss always generating the same graph?when I change the parameters and the name of text file? library(MASS) dados<-read.table("inverno.txt",header=FALSE) vento50<-fitdistr(dados[[1]],densfun="weibull") png(filename="invernoRG.png",width=800,height=600) hist(dados[[1]], seq(0, 18, 0.5), prob=TRUE, xlab="Velocidade

Hii, I will create boxplots from matrices. I have the following data sets: 5.0 1.78 2.99 2.019 0 10.0 1.79 3.00 1.744 0 15.0 1.78 2.98 1.936 0 20.0 1.78 2.99 1.975 0 25.0 1.73 2.91 3.591 0 30.0 1.79 3.00 1.966 0 35.0 1.79 3.00 2.451 0 40.0 1.79 3.00

Hello all! I have a problem to extract values greater that for example 1820. I try this code: x[x[,1]>1820,]->x1 Please help me! Thank you! The data structure is: structure(c(2.576, 1.728, 3.434, 2.187, 1.928, 1.886, 1.2425, 1.23, 1.075, 1.1785, 1.186, 1.165, 1.732, 1.517, 1.4095, 1.074, 1.618, 1.677, 1.845, 1.594, 1.6655, 1.1605, 1.425, 1.099, 1.007, 1.1795, 1.3855, 1.4065, 1.138, 1.514,

I'm getting three failures. TEST-FAIL: exec /home/rkotler/llvmpb3/build/projects/test-suite/SingleSource/UnitTests/Vector/SSE/sse.expandfft TEST-RESULT-exec-time: user 0.3200 TEST-RESULT-exec-real-time: real 0.3172 TEST-FAIL: exec /home/rkotler/llvmpb3/build/projects/test-suite/SingleSource/UnitTests/Vector/SSE/sse.stepfft TEST-RESULT-exec-time: user 0.4000

Hello all! I have a problem with R. I try to merge data like this: structure(c(2.1785, 1.868, 2.1855, 2.5175, 2.025, 2.435, 1.809, 1.628, 1.327, 1.3485, 1.4335, 2.052, 2.2465, 2.151, 1.7945, 1.79, 1.6055, 1.616, 1.633, 1.665, 2.002, 2.152, 1.736, 1.7985, 1.9155, 1.7135, 1.548, 1.568, 1.713, 2.079, 1.875, 2.12, 2.072, 1.906, 1.4645, 1.3025, 1.407, 1.5445, 1.437, 1.463, 1.5235, 1.609, 1.738, 1.478,

Dear all, I work with R Version 2.0.0 on Machine hardware: sun4u OS version: 5.9 Processor type: sparc Hardware: SUNW,Sun-Blade-1000 and I have a very simple data frame (called OR) with the following variables: > sapply( OR, class) X ci FTyp "factor" "numeric" "factor" (In OR$ci there are some Inf-values. OR's

R-help, I'm using the "update" command for a multiple regression model and it is just not working: > update(model1, . ~ . – temp:wind:rad,data=ozone.pollution) Error: unexpected input in "model2<-update(model1, . ~ . –" > summary(model1) Call: lm(formula = ozone ~ temp * wind * rad + I(rad^2) + I(temp^2) + I(wind^2), data = ozone.pollution) Residuals: