search for: 0.0000e

Dear all: I attached the dataset with this email and post codes as below. My questions is related to the 'col=temp.col' for the line and pch in my code, I have 4 IDs, 10 DIDs and each ID include different DIDs, for example, first ID has 3 DIDs, then the color is the first three colors(black, red, green) in the first plot, but in the second plot, why the color change to pink which is

R 2.15.1 OS X and Windows Colleagues, I have a file that looks that this: TABLE NO. 1 PTID TIME AMT FORM PERIOD IPRED CWRES EVID CP PRED RES WRES 2.0010E+03 3.9375E-01 5.0000E+03 2.0000E+00 0.0000E+00 0.0000E+00 0.0000E+00 1.0000E+00 0.0000E+00 0.0000E+00 0.0000E+00 0.0000E+00 2.0010E+03 8.9583E-01

Dear all: I have been thinking to import below one data file (.txt)into R by read.table(..,skip=1, header=T). But How can I deal with the repeated rows of TABLE NO.1 and names of data variables in the middle of this data file. The similar block will be repeated 100 times, here only show 4 of them and within each block, data records also can vary, here only paste 4 rows for example. I appreciate

Dear all: I have been thinking to import below one data file (.txt)into R by read.table(..,skip=1, header=T). But How can I deal with the repeated rows of TABLE NO.1 and names of data variables in the middle of this data file. The similar block will be repeated 100 times, here only show 4 of them and within each block, data records also can vary, here only paste 4 rows for example. I appreciate

R 2.15.1 OS X Colleagues, I am reading a 1 GB file into R using read.table. The file consists of 100 tables, each of which is headed by two lines of characters. The first of these lines is: TABLE NO. 1 The second is a list of column headers. For example: TABLE NO. 1 COL1 COL2 COL3 COL4 COL5 COL6 COL7 COL8 COL9 COL10

Dear ReXperts, I have the below text file output. I need to extract the T, QC, QO, QO-QC and WT columns for the data between T = 10 and T=150. Any ideas? Thanks in advance. ======================================================================================== 1 D C ---CAT-- T THETA QC QO QO-QC QC/QO WT FSD 8 1 0 1.0000E+01

System info: Linux slackware R Version 1.5.1 (2002-06-17) ESS 5.1.21 Emacs 21.2.1 ------------------- Colleagues I have some text files in a certain directory and want to process them sequentially. So I want to pass the filename identifier into a function and loop through the processing of each file in turn.I've called the file identifier f in this code segment: image.dvm <- function

Hello, Are there any R functions available for performing a serial correlation test for short time series (e.g, series having between 10-14 observations)? Many thanks! Isabella R. Ghement, Ph.D. Ghement Statistical Consulting Company 301-7031 Blundell Road, Richmond, B.C., Canada, V6Y 1J5 Tel: 604-767-1250 Fax: 604-270-3922 E-mail: isabella at ghement.ca Web: www.ghement.ca -----Original

Greetings, I am working in the sem package on a model with 3 exogenous variables (2 are nominal-categorical), and 4 endogenous, continuous variables. To use sem with the nominal variables, I created dummy variables. Now, in my sem output I have estimates for path coefficients for the relationship between each level of the nominal variables and the endogenous variables they are associated

Hi there, as a student sociology, I'm starting to learn about SEM. The course I follow is based on LISREL, but I want to use the SEM-package on R parallel to it. Using LISREL, I found it to be very usable to be able to see the total direct and total indirect effects (standardized and unstandardized) in the output. Can I create these effects using R? I know how to calculate them

#### I checked through every 3 factor * 3 loading case. #### While, 4 factor * 3 loading failed. #### the data is 6 factor * 3 loading require(sem); cor18<-read.moments(); 1 .68 1 .60 .58 1 .01 .10 .07 1 .12 .04 .06 .29 1 .06 .06 .01 .35 .24 1 .09 .13 .10 .05 .03 .07 1 .04 .08 .16 .10 .12 .06 .25 1 .06 .09 .02 .02 .09 .16 .29 .36 1 .23 .26 .19 .05 .04 .04 .08 .09 .09 1 .11 .13 .12 .03 .05 .03

Dear List, I will appreciate any advice regarding how to convert the following numbers [I got in return by taxondive()] in numeric integers without the e.g. 6.4836e+01 abbreviations. Thank you very much in advance, Gian > taxa_dive Species Delta Delta* Lambda+ Delta+ S Delta+ Nat1 5.0000e+00 6.4836e+01 9.5412e+01 6.7753e+02 8.7398e+01 436.99 Nat2

Dear Rxperts, I have the following data: Study Study.Name C Category TC Time QC QO SD FSD Theta 1 NONE 0 P(22) 0 0.00 7.5596 0 0 8.0361e-03 0 1 NONE 6 G(50) 0 0.00 1.0000 0 0 0.0000e+00 0 1 NONE 2 F(02) 0 0.00 100.0000 0 0 0.0000e+00 0 1 NONE 3 F(03) 0 0.00 13.2280 0 0 1.6732e-02 0

Hi, I am a total beginner with this whole thing so please have patience! I am trying to run an S-plus program with a certain line: spline(1:nrow(y), y[,1],n=100); This crashes with: Error: NAs in foreign function call (arg 8) Apparently, this is caused by the last command of spline: u <- seq(xmin, xmax, length.out = n) .C("spline_eval", z$method, length(u), x = u, y =

Hello, I have a bar plot where I am already using colour to distinguish one set of samples from another. I would also like to highlight a few of these bars as ones that should be looked at in detail. I was thinking of using hatching, but I can't work out how or if you can have a background colour and hatching which is different between bars. Any suggestions on how I should do this? Thanks

Hi, I am having problems trying to assess the significance of random terms in a generalized linear mixed model using lme4 package. The model describes bird species richness R along roads (offset by log length of road log_length) as a function of fixed effects Shrub (%shrub cover) and Width (width of road), and random effect Site (nested within Site Cluster). >From reading answers to previous

Dear R-Gurus I am a PhD student from South Africa working on chimpanzee behaviour. I am looking at patterns of shade utilization and am using generalized linear mixed models to examine the effects of various factors on whether chimpanzees choose to spend time in the sun or shade. I realise that the lme4 package and the outputs of the lmer functions have been discussed ad nauseum but I have been

Dear R-help-list, I have a problem in which the explanatory variables are categorical, the response variable is a proportion, and experiment contains technical replicates (pseudoreplicates) as well as biological replicated. I am new to both generalized linear models and mixed- effects models and would greatly appreciate the advice of experienced analysts in this matter. I analyzed the

I've seen a number of problems like this over the years. The fact that the singular values of the Jacobian have a ration larger than the usual convergence tolerances can mean the codes stop well before the best fit. That is the "numerical analyst" view. David and Jeff have given geometric and statistical arguments. All views are useful, but it takes some time to sort them all out and

I am not as expert as John, but I thought it worth pointing out that the variable substitution technique gives up one set of constraints for another (b=0 in this case). I also find that plots help me see what is going on, so here is my reproducible example (note inclusion of library calls for completeness). Note that NONE of the optimizers mentioned so far appear to be finding the true best