similar to: lmList and lapply(... lm) different std. errors

I am trying to fit a very simple broken stick model using the package "segmented" but I have hit a roadblock. > str(data) 'data.frame': 18 obs. of 2 variables: $ Bin : num 0.25 0.75 1.25 1.75 2.25 2.75 3.25 3.75 4.25 4.75 ... $ LnFREQ: num 5.06 4.23 3.50 3.47 2.83 ... I fit the lm easily: > fit.lm<-lm(LnFREQ~Bin, data=id07) But I keep getting an error

Hi all, Suppose I want to set the values in a column to the log of the values of another column like so: object$LogDist <- log10(object$Distance) How do I loop through the objects if I have object1, object2, etc to perform this function? object1$LogDist <- log10(object1$Distance) object2$LogDist <- log10(object2$Distance) object3$LogDist <- log10(object3$Distance) I was trying to

Hello, I have a data set with 9700 records, and 7 parameters. The data were collected for a survey of forest communities. Sample plots (1009) and species (139) are included in this data set. I need to determine how species are accumulated as new plots are considered. Basically, I want to develop a species area curve. I've included the first 20 records from the data set. Point

Dear List, I'm getting weird and unexpected behaviour using time and %%, or %/%. It's likely I'm not appreciating the nuances of floating point arithmetic. Or it could be a bug. I'm running > R.version _ platform x86_64-redhat-linux-gnu kernel 2.6.33.8-149.fc13.x86_64 arch x86_64 os linux-gnu system x86_64, linux-gnu

Hello, first of all, thanks to LT for \pkg{codeutils}. I agree that it is indeed very useful to identify errors and also to encourage re-thinking past solutions. My problem: I want to compare different sets of related sub-functions which should be used alternatively by the same top-level function. Sets of related functions should be bound together (as lists) and the workspace should be as clean

I'm having trouble with some catch per unit effort data (CPUE, fisheries data). Some of the samples were "retained" and some "unretained," and they are entered as 2 separate entries for the same sampling event (Date and time). I want to calculate the total CPUE (so sum the "retained" and "unretained" number for each sampling event) and am having troubld

Dear All, I would like to ask a couple of questions on a LME model. I tested 4 selection lines at 4 food concentrations against a standard competitor stock. I had 3 replicate cages per selection line. In each cage I have 10 vials. I counted the number of wild type flies and competitor stock emerging in each vial. My main question is: is there any difference between selection lines? I did fit

There seems to be 2 functions call ecdf... http://lib.stat.cmu.edu/S/Harrell/help/Hmisc/html/ecdf.html http://127.0.0.1:11885/library/stats/html/ecdf.html How do I get the one ecdf {Hmisc} to run instead of the ecdf {stats} A pointer in the right direction would be greatly appreciated. Tried to instal Hmisc but got this message, so I assume I have it > utils:::menuInstallPkgs() Warning:

I cannot understand the following error printed out when I try to get the extrema of my time series. I would appreciate some suggestion as I really cannot interpret the error. I might not be using a proper set of parameters in calling such functions. I am learning by doing ... > aa.peak <- wavCWTPeaks (aa.tree) Error in `row.names<-.data.frame`(`*tmp*`, value = c("1",

Greetings All. Once again, I am probably missing something fairly accessible, but since I can't find it I'd welcome advice! I have a dataframe derived from a text file of data in tabular format. For one of the variables, say X, I want to select the subsets which in which X equals a particular value. Such values are given in the text file like: 2.3978953, and each such value will occurr

lgamma(x) and lfactorial(x) are defined to return ln|Gamma(x)| {= log(abs(gamma(x)))} or ln|Gamma(x+1)| respectively. Unfortunately, we haven't chosen the analogous definition for lchoose(). So, currently > lchoose(1/2, 1:10) [1] -0.6931472 -2.0794415 NaN -3.2425924 NaN -3.8869494 [7] NaN -4.3357508 NaN -4.6805913 Warning message: In

Dear R-helpers, I have a data.frame (bcpe.lat.m) containing 13 countries, ages 0-50yrs per month, and the corresponding mu&sigma (see below). * I would like to limit the age range to include all 12 months for the 1st 5 years and only whole years for all ages thereafter for each of the countries present in the data frame. * I would like to create separate data.frames according

Greetings: It would seem to me that the three arguments "a", "c" and "p" ought to produce the same result with a data frame that doesn't have any missing data which is not the case. What am I doing wrong or what don't I understand? > tmp <- data.frame(vol,con,mot,esp,pri,sec) > tmp vol con mot esp pri sec 1 1.00 120 90 78 21 1 2 0.50

Dear All, Suppose I have 2 files: # first one : testid.csv A B C D E > (id<- read.table ("testid.csv",col.name=c("id"))) id 1 A 2 B 3 C 4 D 5 E # second file is the result file I calculate from cor.text, which shows the correlation coefficient. > cor.value.t 1 2 3 4 5 1 1.0000000 0.2156213 0.31000492

Hello everyone, I have a file called "trans" which has 100 records (rows) and 60 columns. I need to make 2 samples (with 5 records in each) out of this file with no replacement, so I used "replicate". The sampling part works fine and I called the outcome "result". my problem is then I need to calculate the correlation matrix for each sample. I used

I'm trying to run an SEM, but I keep getting the following error message. In sem.default(ram = ram, S = S, N = N, param.names = pars, var.names = vars, : Could not compute QR decomposition of Hessian. Optimization probably did not converge. I have 4 latent variables (plant, AMF, abiotic, and soilAgg) with 2 or 4 indicator variables for each latent variable.My model is specified as: >

Hi friends, If someone can find out some time to go through my problem would be really grateful. I have a dataset(dataset1) as shown below:-- recmeanC1 recmeanC2 recmeanC3 recmeanC4 i1 i2 i3 i4 i5 i6 i7 i8 i9 i10 i11 1 NA 1 1.00 1.800000 NA 1 NA 1 1 NA 2 2 2 NA 2 2 2 2 1.00

Dear R What does NaN mean? I recently did a correlation on a batch of data for some reason it didn't like one column cor(sleep,use="complete.obs") BodyWt BrainWt SlowSleep ParaSleep TotalSleep BodyWt 1.00000000 0.95584875 -0.3936373 -0.07488845 -0.3428373 BrainWt 0.95584875 1.00000000 -0.3867947 -0.07427740 -0.3370815 SlowSleep -0.39363729

Hi friends, I have questions about printing a pretty big size matrix. As you could see from below, the matrix wasn't showed in R at full size (11X11), but it was cut partly into three smaller matrices (11X4,11X4,11X3). I'm wondering if there is a way to show the whole matrix with dimension 11X11, do you know how to make it? If R really couldn't fit the full big matrix at once, what

There is a bug in Matrix package, please check it, thanks! Matlab result: x = 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 >> lu(x) ans = 21.0000 22.0000 23.0000 24.0000 25.0000 0.0476 0.9524 1.9048 2.8571 3.8095 0.7619