similar to: data messed up by read.table ? (PR#9779)

I'm not sure if this is a bug, or if I'm doing something wrong. =20 =46rom the worms dataframe, which is at in a file called worms.txt at =20 http://www.imperial.ac.uk/bio/research/crawley/therbook <http://www.imperial.ac.uk/bio/research/mjcraw/therbook/index.htm>=20 =20 the idea is to extract a subset of the rows, sorted in declining order of worm density, with only the maximum

All, I'm trying to analyze the results of a reciprocal transplant experiment using lme(). While I get the error-term right in aov(), in lme() it appears impossible to get as expected. I would be greatful for any help. My experiment aimed to identify whether two fixed factors (habitat type and soil type) affect the development of plants. I took soil from six random sites each of two types

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:

Would anybody be able to advise on which package would offer the best approach for producing a model able to predict the probability of species occupation based upon a range of variables, some of them catagorical (eg. ten soil types where the numbers assigned are not related to any qualitative/quantitative continuum or vegetation type) and others continuous such as field size or vegetation height.

Why are the results not reliable? ________________________________ From: ESCHEN Rene [mailto:rene.eschen@unifr.ch] Sent: Wednesday, August 23, 2006 3:48 AM To: Spencer Graves; r-help@stat.math.ethz.ch Cc: Doran, Harold Subject: RE: [R] Random structure of nested design in lme The output of the suggested lmer model looks very similar to the output of aov, also when I ran the model

Hello all, I have a *.csv file that looks like this (actual file is orders of magnitude larger): Site taxa no.ind forest LMA 1 forest LCY 1 forest SCO 1 meadow LMA 2 meadow LCY 1 meadow PNT

Dear All, I would like to make partial sums (or means or any other function) of the values in intervals along a sequence (spatial transect) where groups are defined. For instance: habitats<-rep(c("meadow","forest","meadow","pasture"),c(10,5,12,6)) observations<-rpois(length(habitats),2)

I have a vector of land cover class data from a GIS: > landcov[1:10,2] #the first ten examples of a large (100k+) object 1 2 3 4 5 6 7 8 9 10 12 12 01 12 01 15 15 15 15 15 etc. I also have a lookup table for the class data that gives the cover type as a string: > cnd.names #the look up table, i.e., landcov[3,2] == 1 == "Montane Meadow" CndVal

dear R-friends, i`ve got a large dataset of vegetation-samples with about 500 variables(=species) in the following format: 1 spec1 1 spec23 1 spec54 1 spec63 2 spec1 2 spec2 2 spec253 2 spec300 2 spec423 3 spec20 3 spec88 3 spec121 3 spec200 3 spec450 . . this means: sample 1 (grassland) with the species (=spec) 1, 23, 54, 63 is it possible to get a following data-structure for further

Dear List, I am realtively inexperienced so i apologise in advance and ask for understanding in the simplicity of my question: I have data on the amount of grass per km in a cell ( of which i have lots) "grass" and for each cell i have x/y coordinates - required due to spatial autocorrelation Cells can be classfied in a hierarchical nature into AREAS and STATES i.e Cell 1, Cell 2,

hello all R experts, how do I calculate the reliability between the two groups using the ICCs? I'll appreciate your reply, Thanks Sincerely, Supreet kaur, Biomedical research engineer, Nationwide Childrens Hospital, Columbus, OH (614)355-3509 [[alternative HTML version deleted]]

I am new to R. I have a data set like this (given below is a fictional dataset): AgeCat FINWT 1 98 2 62 1 75 3 39 4 28 2 47 2 66 4 83 1 19 3 50 I need to calculate the weighted distribution of the variable AgeCat. In SAS i can do: proc freq data=ageval; tables agecat; weight finwt; run; What or is there an equivalent in R? TIA, Krishnan -- Krishnan Viswanathan 1101 High Meadow Dr

I am trying to put my app on heroku, following the instructions, when I get here I get this error: $ git push heroku master Enter passphrase for key ''/c/Users/Laurence/.ssh/id_rsa'': Counting objects: 277, done. Delta compression using up to 2 threads. Compressing objects: 100% (246/246), done. Read from remote host heroku.com: The connection was aborted fatal: sha1 file

Hi all Bear with me on this one... We have a problem connecting to a specific port via Oracle TNSPING There are two PC's in our office that are on the same network as the server (i.e. my desktop PC can not get to the server) The server has multiple network interfaces, the primary is a gigabit fibre card on IP xx.16. The secondary is a megabit card on IP xx.80 The tnsping command fails

I've written a function that regularly throws the "cannot allocate vector of size X Kb" error, since it contains a loop that creates large numbers of big distance matrices. I'd be very grateful for any simple advice on how to reduce the memory demands of my function. Besides increasing memory.size to the maximum available, I've tried reducing my "dist" objects to 3

I have the following sample dataset (CSV input here:http://goo.gl/YR8LP. CSV output here: http://goo.gl/EFCC8) which I want to transform as follows. For each person in a household I want to create two new variables OrigTAZ and DestTAZ. It should take the value in TripendTAZ and put that in DestTAZ. For OrigTAZ it should put value of TripendTAZ from the previous row. For the first trip of every

From Peter Dalgaard announcement earlier today. CHANGES IN R 3.4.3: INSTALLATION on a UNIX-ALIKE: * A workaround has been added for the changes in location of time-zone files in macOS 10.13 'High Sierra' and again in 10.13.1, so the default time zone is deduced correctly from the system setting when R is configured with --with-internal-tzcode (the default on

Hi, I am trying to work with the ape package, and there is one thing I am struggling with. When calling the *read.GenBank()* function, I can get it to work with an object created like this: *>x <- c("AY395554","AY611035", ...)* *>read.GenBank(x)* However, I am trying to use the function to fetch several hundred sequences at once. So I have been testing with small

Mark Thanks for pointing this out. I did a default installation of R. Does this mean that I need to reinstall from the command line? Dennis Dennis Fisher MD P < (The "P Less Than" Company) Phone / Fax: 1-866-PLessThan (1-866-753-7784) www.PLessThan.com <http://www.plessthan.com/> > On Nov 30, 2017, at 6:42 PM, R. Mark Sharp <rmsharp at me.com> wrote: > >

hi folks, in my (unlucky) first test of ogg vs other encoders, i found a case where wma and mp3pro sound much better than ogg at 64k. can anyone suggest a setting that i haven't tried yet that can rival the wma and mp3pro samples at 64k? it's the "gravel effect" that is troublesome. the part in question is the first 15 seconds of this wave file: