similar to: logistric regression: model revision

Hello, I need some help getting started with data analysis. I’m having trouble getting R to read my data file. I’ve referred to various R help documentation, the website, and FAQs, but I don’t see my situation listed. I saved an Excel file (post-2007 Excel version) of data as a “.csv” file. However, the file still appears in column format when I open it. Does that happen when you save a an

Hello R folks, I’m looking to produce a confusion matrix using the command: cmx(PData,threshold=0.49,na.rm=FALSE) for a logistic regression model (1 is habitat, 0 is nonhabitat). To compile my PData data file (csv file) (as in the example above), I’m using the output of the predict(glm) function. Is there a way to export the output of the predict function (which formats itself as shown below)

Hello, I am new and am having a hard time getting the proper syntax for output from loops. I am working on a simulation to generate a null expectation of bee behavior. Pieces of it work. The part that I am having specific difficulty is in output of a vector from within the while loop that I am using. Basically the simulation works as such: I have a starting point and a neighbor matrix and a

Dear R users, I have created a Loess surface in R, in which x is relative longitude by miles, y is relative latitude by miles, and z is population density at the neighborhood level. The purpose is to identify some population centers in the region. I'm wondering if there is a way to determine the coordinates (x,y) of each center, so I can know exactly where they are. Let me use the

Dear list, i'm a new R user, so I apologize if the topic is already being addressed by some other user. I'm trying to determine if the reproductive success of a species of bird is related to a list of covariates. These are the covariates: ? elev: elevation of nest (meters) ? seadist: distance from the sea (meters) ? meanterranova: records of temperature ? minpengS1: records

Hello, I?m using zero-inflated Poisson regression via the zeroinfl() function to analyze data on seed-set of plants, but for some reason, I don?t seem to be getting the output for all three levels of my two categorical predictors. More about my data and model: My response variable is the number of viable seeds (AVInt), and my two categorical predictors are elevation (Elev) and Treatment

I am sorry if this question is vague or uninformed. I am just learning R and struggling. I am using the book Hierarchical Modeling and Inference in Ecology and they provide examples of R code. I have the following code from the book but when I run it I don't get any output. I cannot get the values of 'out' to show up. Basically, I just want to see my estimates for b0,

Hi all, I was recently writing a script to identify the value and id of the maximum observation in a sliding window when I ran into some unexpected behavior. I have included an example. > test <- c() > test$elev <- c(1:200) > test$i <- 1 > test$window <- 10 The following works for me: > check.max <- function(x){obs.max <- x$elev[x$i:x$i+x$window]; obs.max}

Dear R community, I'm having hard time to understand the kde function in "ks" package. Let me use a 3-dimensional kernel smooth example to explain my question using the elevation data in geoR. ### here is what I did ### library(ks) require(geoR) data(elevation) elev.df <- data.frame(x = elevation$coords[,"x"], y = elevation$coords[,"y"], z = elevation$data)

Dear exports,I have created a hypsometric curve (area-elevation curve) for my watershed by using simple command hypsometric(X,main="Hypsometric Curve", xlab="Relative Area above Elevation, (a/A)", ylab="Relative Elevation, (h/H)", col="blue")It plots the hypsometric curve in "RGraphics window", My question is how can I export values which is used

Hola a tod en s. Se trata de un tema que lleva tiempo rondándome la cabeza, pero que nunca he encontrado una solución. Se que existe el paquete survey, pero me gustaría saber si existe algo más sencillo. Por ejemplo, estaba analizando los últimos datos de la encuesta de equipamientos tecnológicos del INE y dicho fichero tiene dos variables con factores de elevación, una para hogares y otra para

Dear all, I have built glm models based on presences/absences and a number of predictor maps and would like to compute habitat suitability based on the modelled coefficients. I thought this is pretty straight forward and wanted to use predict() and supply the new data in a data frame, with one column for each predictor. However, I do get an error msg warning me that the number of rows for

Hello: I would like to superimpose vector polygons (state outlines) from a Shape file on top of a satellite image, imported into a SpatialGridDataFrame from GEOTIFF via gdal_translate and readGDAL. When I plot polygon and point shape files in R, into SpatialPointDataFrame and SpatialPolygonDataFrame, the two feature sets line up geographically, so it seems logical that a SpatialGridDataFrame

Hello! I've installed Samba as a PDC and followed all documentations I've found helpful on the internet! It looks like everything runs nicely now on my Debian server with Linux 2.4.21 and Samba 3.0beta1 except when it comes to groups. I have i.e. the following share: [Learning] path = /home/share/learning write list = @personal, @admin, @installer force group =

1. I'm attempting to test for Random Effects. I've grouped the data on subject (grid) but want to use lme to build the model without subject as a RE then add it and do anova between the 2 models. This is the result I get and it appears it's adding Random Effects. tmp.dat4 <- groupedData(Trials ~ 1 | grid, data = tmp.dat4) mod2a <- lme(Trials ~ factor(group_id) + reversal,

Hi List, I am trying to plot a grid with an overlayed height. I have a dataframe with four variables: x,y,gridvalue,height. The dataframe has 2.5mio observations (ie grid points), I assign colors through the gridvalue using map_color_gradient thus producing: x,y,gridvalue,height,gridcol as variables of the dataframe. The grid dimensions are 1253 x 2001 (=2507253 data points). My attempts with

I'm completely new at R... I have sinkhole survey data (lat, long, and elevation) and have been trying to plot a rotatable 3d plot for several hours... cannot get it right. Examples I see tend to be grid data (one elevation value per grid cell); however, my data are more random (known elevations at known (but random) x-y positions). Data format is tab separated, i.e.: lat long

Hi, I receive the following warning message when I run a poisson GLM in R: "glm.fit: fitted rates numerically 0 occurred" The model summary is shown below. The variable 'Species' consists of counts of different species ranging from 0 to 4. I suspect this may have something to do with the warning message but I'm not sure. Can anybody help? Thank you! Anna Call:

Hi, I've done some searching where others have had trouble with this error (or "warning" actually), but I'm unable to solve my problem. I have a data sheet with 13 columns and 36 rows. Each column has exactly the same number of rows. I've created glms and now want to do cross-validation on 2 of them. Please be gentle-- I'm new to R (and statistics, too, for that

Dear All, I have a question on overlaying a filled.contour (e.g. on soil properties data) and contour (by elevation) in one graph. Both have the same z matrix dimension. I'm able to overlay both graph, but the plots dimension did not overlap well on the same plots. How can I have both filled.contour and contour on the same graph? The commands that I have written are as follows: