similar to: Multi-figure plotting

Hello, I have conducted an SEM in which the resultant standardized path coefficients are much higher than would be expected from the raw correlation matrix. To explore further, I stripped the model down to a simple bivariate relationship between two variables (NDVI, and species richness), where it's my understanding that the SEM's standardized path coefficient should equal the correlation

Hi All, I'm running into a problem with GAM (in the MGCV package). When I try to estimate the model, I get the following error message: 1> fit <- gam(ndvi~s(rain)+s(temp)+s(rainl1)+s(rainl2)+s(rainxY)+s(rainl1xY)+s(rainl2xY)+s(tempxY), data=dsub, weights=wvec) Error in while (mean(ldxx/(ldxx + ldss)) > 0.4) { : missing value where TRUE/FALSE needed Using

Hi weekend R helpers, *Is it possible to get a ylabel on the right hand side axis ==> axis(4)? Thankx, Jan opar <- par(mfrow = c(2,1)) plot(ts.Origi[,1],ylab='NDII', main=name) # Add the legend text in the right order legend.txt <- c("NDII", "Inverse KBDI") legend(2001.8,0.29, legend.txt,col=c(1,2), lty=1)

Hello R-users, I'm currently facing a pretty hard problem which I'm hopping you'll be able to help me with. I'm using R to create images. That alone is not the problem, the problem is that I'm using R to create 168 000 images... My code (which is given below) use different package (raster and rgdal) to import a image (size 20gig) and divide it into 168 000 pictures that are

I am using the R-package MODISTools (different than MODIS) and am having a lot of difficulty troubleshooting my code. I have spent awhile going through MODISTools tutorials, searching for my error code, looking at the source code. However, I have not been able to find any relevant information related to my error message. The study I am currently working on involves a herd of 200 African buffalo

I am using MODIS Tools and am having a lot of difficulty troubleshooting my code. I am a PhD student studying African buffalo in Kruger National Park, South Africa. The study I am currently working on involves a herd of 200 African buffalo caught every six months for 4 years. I am trying to use EVI and NDVI to assess seasonal variation thus I would like mean EVI and NDVI for each observation

I have and they have not yet replied - however that was only two or three days ago. I have included a code example. > On Jun 22, 2017, at 8:25 PM, David Winsemius <dwinsemius at comcast.net> wrote: > >> >> On Jun 22, 2017, at 4:44 PM, Caroline <gliddeca at science.oregonstate.edu> wrote: >> >> I am using the R-package MODISTools (different than

> On Jun 22, 2017, at 4:44 PM, Caroline <gliddeca at science.oregonstate.edu> wrote: > > I am using the R-package MODISTools (different than MODIS) and am having a lot of difficulty troubleshooting my code. I have spent awhile going through MODISTools tutorials, searching for my error code, looking at the source code. However, I have not been able to find any relevant information

Dear all, I am attempting to explain patterns of arthropod family richness (count data) using a regression model. It seems to be able to do a pretty good job as an explanatory model (i.e. demonstrating relationships between dependent and independent variables), but it has systematic problems as a predictive model: It is biased high at low observed values of family richness and biased low at

On 6/22/2017 7:05 PM, Caroline wrote: > ##MODISTools example > library(MODISTools) > library(lubridate) > setwd('~/Documents/Modis data') > > #####MODISTools with buffalo data > > ###Read in data rename for easier coding > tbdata <- read.csv('~/Desktop/All TB data for EVI, NDVI.csv') Since this dataset is only on your desktop it cannot help us

##MODISTools example library(MODISTools) library(lubridate) setwd('~/Documents/Modis data') #####MODISTools with buffalo data ###Read in data rename for easier coding tbdata <- read.csv('~/Desktop/All TB data for EVI, NDVI.csv') firstobs <- subset(tbdata, capture.ID == 'B1-1108') firstobs <- firstobs[,c(1,2,2,3,4)] colnames(firstobs) <- c('id',

Dear List, I have a list of 600+ *.gz files that I would like to extract and read the geotiffs contained within them. I tried using the untar() function to simplify this task but I am stumped by an error. I've combed the Internet for a solution without luck. The details are below, and any help in solving this matter is appreciated. > files = list.files(path = "J:/GIMMS/NDVI",

Please read up [1][2][3] on what constitutes reproducibility. A sample of data that triggers the problem is essential. [1] http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example [2] http://adv-r.had.co.nz/Reproducibility.html [3] https://cran.r-project.org/web/packages/reprex/index.html -- Sent from my phone. Please excuse my brevity. On June 23, 2017 6:54:48

1. You should always cc the list unless there is a clear reason not to. 2. You still have failed to follow the posting guide: You say you have difficulty troubleshooting your code, but you have shown us no code. You got an error message that seems explicit, but with neither code nor data, I do not know whether anyone can make sense of it. In any case, I certainly cannot. Cheers, Bert Bert

Hi, I have been running the same code without problem for the last few days, changing data sets etc with no issue. Today I changed the covariates for the model and am now getting this error message: Error in `contrasts<-`(`*tmp*`, value = contr.funs[1 + isOF[nn]]) : contrasts can be applied only to factors with 2 or more levels Everything in the code looks the same to me, but I'm a

Dear R Helpers, Currently I'm working with the ts package of R and created a TimeSerie from pixels extracted from satellite imagery(S10 NDVI data, 10 daily composites). I'm trying to decompose this signal in different signals (seasonal and trend). When testing out the STL method is says => Only univariate timeseries are allowed, but the current Timeserie I'm using is univariate!

Hi All, I am busy using R to do some regression modelling and have been using plot(x,y,"") to visualise my variables. I would now like to label my points using data stored in the data.frame used for the regression analysis. For example each of my data points is made up of a field measured forest volume value and a remotely sensed vegetation estimate (NDVI). Each point is an enumeration

Dear all, We are doing some research about the time series analysis of NDVI, and we found the NDVITS package which is a very great tool. Unfortunately when we run it, after TimeSeriesAnalysis it asks to enter "Village or Country". library("ndvits", lib.loc="/home/vahe/R/i686-pc-linux-gnu-library/2.15")

Dear All, Anybody know if *4253H twice filter* is implemented in R? *Description of filter:* Applies a series of running medians of varying window size and a weighted average filter, with re-roughing, to the NDVI time series *Reference*: Velleman, P. (1980). Definition and comparison of robust nonlinear data smoothing algorithms. Journal of the American Statistical Association.. Thanks Julio

Hi all, I created a graph by plotting 4 time series on top of each other but don't know how to add extra axes on the right hand side of the plot (or leftside). For the first two time series it axis are plotted but the last two time series don't have and axis. How can these be added and where? e.g. par(mfrow=c(1,1)) plot(timeserie1) par(new=T) plot(timeserie2,