similar to: Spatial Autocorrelation for point data

Dear all, Is there a simple trick to read in data with the following format and create a Time Serie object of it? Date CountOfField2 5/10/1998 7 5/11/1998 5 5/12/1998 2 5/14/1998 1 5/15/1998 1 5/19/1998 1 5/20/1998 1 5/21/1998 1 5/24/1998 2 5/25/1998 1 5/26/1998 2 .... 2002 ... R should recognize that some dates are not available...(NA). You can define start and end date Ok, and frequency= 365

Dear R-list, Is there a function or technique by which the probability (or log odds) range of a logistic model (fit <- lrm(Y~X)) can be derived? The aim is to obtain min & max of the estimated probabilities of Y. Could summary.Design() be used for that or is there another method/trick? Thanks, Jan _______________________________________________________________________ ir. Jan

Dear all, When saving a plot with the dev2bitmap command: name <- c("test.jpeg") dev2bitmap(name,type="jpeg",height=8,width=13,res=400) Everything seems to be ok... After importing this picture in CORELDRAW (for a poster A0) format the resolution and colors are not optimal. How can I save pictures (colors/resolution) optimally for import into CorelDraw for an

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,

Dear R list, From the lrm() binary logistic model we derived the G2 value or the likelihood-ratio chi-squared statistic given as L.R. model, in the output of the lrm(). How can this value be penalized for non-linearity (we used splines in the lrm function)? lrm.iRVI <- lrm(arson ~ rcs(iRVI,5), penalty=list(simple=10,nonlinear=100,nonlinear.interaction=4)) This didn’t work

Dear r-list, When I try to plot the following 3D lrm fit I obtain only arrows with labels on the three axes of the figure (without values). fit <- lrm(y ~ rcs(x1,knots)+rcs(x2,knots), tol=1e-14,X=T,Y=T) dd <- datadist(x1,x2);options(datadist='dd'); par(mfrow=c(1,1)) plot(fit,x1=NA, x2=NA, theta=50,phi=25) How can I add values to the axes of this plot? (axes with the

Dear R-list, *When comparing two logistic regression models with the anova CHi test, I obtain the following error: (there are no NA's in the time series). How can this be solved such that I can compare two models on the same dataset were different explanatory variables are used? l.KBDI <- glm(zna.arson2 ~ zna.KBDI,family = binomial) l.NDWI <- glm(zna.arson2 ~ zna.NDWI,family

Dear, Thanks for the previous tips about 'its' for importing the following data. 5/10/1998,7 5/11/1998,5 5/12/1998,2 5/14/1998,1 5/15/1998,1 5/19/1998,1 5/20/1998,1 1. When using the following command; test<-readcsvIts('Fires98.csv',informat=its.format("%m/%d/%Y"),header=FA LSE) the function reads in the data from the csv file as; V2 05/10/1998 7

Hi all, How can the label of the x-axes in the plot() of a stl.object be adapted? e.g., When plotting: plot(stl(nottem, "per")) In the labels of the x-axes is “time”. How can this be changed to e.g., “Time (dekade) “? It does not work with xlab or others anymore… Thanks, Jan _______________________________________________________________________ Ir. Jan Verbesselt Research

Dear R-helpers, Is it possible to create a type of 'movie' in R based on the output of several figures (e.g., jpegs) via the plot() function. I obtained dynamic results with the plotting function and would like to save these as a movie (e.g., avi or other formats)? Regards, Jan _________________________________________________________________ Ir. Jan Verbesselt Research

Hi, When running z <- plot(fit, age=NA, cholesterol=NA, perim=boundaries, method='image') Legend(z, fun=plogis, at=qlogis(c(.01,.05,.1,.2,.3,.4,.5)), zlab='Probability') And after pointing the cursor to the plot() screen in R, I obtain the following message: Using function "locator(2)" to place opposite corners of image.legend Error in

Dear R-help, How could a cross-correlation plot be optimized such that the relationship between seasonal time-series can be studied? We are working with strong seasonal time-series and derived a cross-correlation plot to study the relationship between time-series. The seasonal variation however strongly influences the cross-correlation plot and the plot seems to be ?rather? symmetrical (max

Hi R-list, I'm working with irregular time series (time series of climate data, daily data 365/6 days a year) and would like to create regular time series from them ( irts e.g. Rain <- irts(as.POSIXct(Climate[,1]),Climate[,5]) to ts e.g. test <- ts(x, start=c(1997,1), frequency=365) ) such that I can find where the gaps (lacking temperature data, ...) are and try

Hi R-help, We are using R 2.2 on Win XP and have a detail question on how the legend can be optimised. We use the following; -> plot(,type="b",...) The lines in the plot do not cross the points. How can we obtain the same effect in the legend? (points without a line through them..) We tried setting the pt.bg to white but this did not help. See script below. thanks, Jan

Dear, When fitting the following model knots <- 5 lrm.NDWI <- lrm(m.arson ~ rcs(NDWI,knots) I obtain the following result: Logistic Regression Model lrm(formula = m.arson ~ rcs(NDWI, knots)) Frequencies of Responses 0 1 666 35 Obs Max Deriv Model L.R. d.f. P C Dxy Gamma Tau-a R2 Brier 701 5e-07 34.49

Hello List, I'm a very new user to the R system. I'm only beginning to learn the basics, but so far I've been able to do little more than try a few examples, and of course begin reading the documentation. My primary motivation for exploring R is the availability of tools like the 'spdep' package for calculating spatial statistics such as Geary's C and Moran's

hi,friends, we all know that moran's I index and Geary'C index can be used to test spatial autocorrelation in both the area data and point data, but i only can find something on how to calculate on the data of area, and can't find the methods to perform it on the point data, could anybody give me some information, thanks in advance! -- Kind Regards, Zhi Jie,Zhang ,PHD Department of

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 R-help, When using the package Design and the plot.Design function all the graphs of an lrm.fit (lrm()) are plotted without a frame (only with axes). How can the frame be added to these plots? In the plot.default function the frame can be added/or removed via the frame.plot=T/F, respectively. e.g., plot(1,axes=T,frame.plot=T). How can this be done with plot.Design(lrm.fit) Thanks,

Hi, I have collected data on trees from 5 forest plots located within the same landscape. Data within the plots are spatially autocorrelated (calculated using Moran's I). I would like to do a ANCOVA type of analysis combining these five plots, but the assumption that there is no autocorrelation in the residuals is obviously violated. Does anyone have any ideas how to incorporate these spatial