similar to: replicated time series - lme?

#short example version of input file with 2 runs and 5 time steps (instead of 17 runs and 500 time steps) run t cover 1 1 0.234306 1 2 0.188896 1 3 0.198193 1 4 0.213959 1 5 0.184952 2 1 0.189316 2 2 0.185631 2 3 0.20211 2 4 0.216064 2 5 0.216064 #calculate the correlation of lag 1 over 17 replicates a<-0 for (i in 1:17) { c<-ts( cover[run==i] ) d<-acf( c, lag=1, plot=F) a<-a+d$acf[2]

I have created a list of tables with the same columns but different number of row. Example (actual list has ~200 elements): > temp1<- data.frame(ID=c("Herb","Shrub"),stat=c(4,5),pvalue=c(.03,.04)) > temp2<- data.frame(ID=c("Herb","Shrub", > "Tree"),stat=c(12,15,13),pvalue=c(.2,0.4,.3)) > L<-list(a=temp1,b=temp2) > L $a

I have a function (see below). This function has one object, ID. If I run the loops by themselves using a character value (ie,"VFFF1-7") instead of the function object, then the loops work fine. However, when I try to insert the character value via the function call, it doesn't work. I don't get an error, but the TotalCover.df dataframe does not update according to the loop

I have a function (see below). This function has one object, ID. If I run the loops by itself using a character value (ie,"VFFF1-7"), then the loops work fine. However, when I try to insert the character value via the function call, it doesn't work. I don't get an error, but the TotalCover.df dataframe does not update according to the loop criteria. Any obvious problems that

Hi, I am having problems trying to assess the significance of random terms in a generalized linear mixed model using lme4 package. The model describes bird species richness R along roads (offset by log length of road log_length) as a function of fixed effects Shrub (%shrub cover) and Width (width of road), and random effect Site (nested within Site Cluster). >From reading answers to previous

Hi Helpers: I have a factor object that has 314k entries of 39 land cover types. (This object can be coerced to characters neatly should that be easier to work with.) > length(foo) [1] 314482 > foo[1:10] [1] Montane Chaparral Barren Red Fir Red Fir [5] Red Fir Red Fir Red Fir Red Fir [9] Red Fir Red Fir 39 Levels:

Dear All I have a problem with the height of the boxes in the key in the following. (The text is over 2 lines to accentuate the problem of no space between the rectangles.) Is there an easy way to put a space between the rectangles; size controls the width but there appears to be nothing for the height? xyplot(1~1, key = list(corner = c(0.8,0.8),

Hopefully the attachment will make it this time... Hi: I am practicing with the attached shapefile and was wondering if I can get some help. Haven't used 'rgdal' and 'maptools' much but it appears to be a great way bring map data into R. Please take a look at the comments and let me know if I need to explain better what I am trying to accomplish. library(rgdal)

I am basically trying to append a value(vector) to one dataframe using a relational value from another dataframe. Obviously, I can use a loop to accomplish this. However, is there a way to vectorize it? Example: > data <- data.frame(c(1,1,1,2,2,2,3,3,3),rep(2,9)); names(data) <- > c("Sample","Score") > meta <-

Hello all, I have a data set where the response variable is the percent cover of a specific plant (represented in cover classes 0,1,2,3,4,5, or 6). This data set has a lot of zeros (plots where the plant was not present). I am trying to model cover class of the plant as a function of both total nitrogen and shrub cover. After quite a bit of research I have come across a conditional approach

Hello useRs, I have some problems when I try to plot a lattice. The lattice has 200 columns (X value) and 5 rows (Y value), with a total of 1000 squares. I want to plot this lattice with the squares having different colours according to a variable value. The variable I want to plot is cover value of a shrub, and it has values between 0 and 1. I want to plot the squares with value 1,

If I have a data frame where a species occupies several rows with different phases such as (both col's ar factors): species,phase Populus tremula,1 Populus tremula,2 Populus tremula,3 Calluna vulgaris,1 Calluna vulgaris,2 Betula alba,1 Betula alba,2 Betula alba,3 Primula veris,1 Primula veris,2 and another df where each species only have one row: species,growth_form Populus tremula,tree Acer

Hi all, I'm using spatstat to investigate the spatial structure of an arid shrub population. The first-order intensity of my data does not appear to be homogenous, so I would like to use inhomogeneous techniques. I realise there is a inhomogeneous K-function available in spatstat, but there doesn't not appear to be one for the pair-correlation function (O-ring statistic). As such I was

Hello I'm trying to create a barplot with a couple of stacked positive values and with one negative value for each group. example: trees<-c(20,30,10) shrubs<-c(12,23,9) veg<-c(2,3,4) soil<-c(-100,-123,-89) example1<-t(cbind(trees,shrubs,veg)) barplot(example1) #this works so far #but now: example2<-t(cbind(trees,shrubs,veg,soil)) barplot(example2) This shows no more

Hi: I am practicing with the attached shapefile and was wondering if I can get some help. Haven't used 'rgdal' and 'maptools' much but it appears to be a great way bring map data into R. Please take a look at the comments and let me know if I need to explain better what I am trying to accomplish. library(rgdal) library(maptools) library(ggplot2) dsn="C:/Documents and

Hi everybody, Well, I really hoped that until now i know how to do a selection ..... but obviously i don't. So risking your laughing at me - here you go. I have a table with lots of vegetation data, and one column specifies in which region the data is. There are only 2 regions, region 1 and region 3. I want to select all data that belong to region 1 and after do some xtabs on it. If i do

Hi, My name is Jos?? Mar??a G??mez, and I am pretty new in R. Thus, I apologize deeply if my questions are extremmely na??ve.I have checked several available books and URL's, without finding any answer. I'm trying to fit Generalized Linear Mixed Models via PQL. Below I provide the structure of my data set. Year and Plot are random variables. Fate is the binomial dependent. I have severe

The shapefile data can be downloaded from the link below: download all the six files and save them on your working directory and make sure the dsn path is set to where the files are saved. My shapefiles are saved on C:/Data. https://secure.filesanywhere.com/fs/v.aspx?v=897263875a6472a99baa Hi: I am practicing with the attached shapefile and was wondering if I can? get some help. Haven't

Hi: I am using a subset of the below dataset to predict PRED_SUIT for the whole dataset but I am having trouble with 'newdata'. The model was created with 153 records and want to predict for 208 records. wolf2 <- structure(list(gridcell = c(367L, 444L, 533L, 587L, 598L, 609L, 620L, 629L, 641L, 651L, 662L, 674L, 684L, 695L, 738L, 748L, 804L, 805L, 872L, 919L, 929L, 938L, 950L, 958L,

Hello all, This may be a simple question to answer, but I'm a little bit stumped with respect to the calculation of the F statistics in nested anovas with unbalanced design in R. In my case, I have 11 vegetation transects (with 1000 10cmx10cm squares), where we estimated shrub cover. We have two different treatments: wildfire (4 transects) and prescribed burning (7 transects) and we want to