search for: 44.2

Hello all, I'm trying to create a 2x2 matrix, 32 times after unlist() so that I can convert the list to matrix. I've looked through the R archive but couldn't find the answer. There is what I've done. > f <- system("ls *.txt", intern=TRUE) > x <- lapply(f, read.table) > x [[1]] V1 V2 1 -27.3 14.4 2 29.0 -38.1 [[2]] V1 V2 1 14.4

I need you help with this problem, I have a data-frame like this: BHID=c(43,43,43,43,44,44,44,44,44) FROM=c(50.9,46.7,44.2,43.1,52.3,51.9,49.3,46.2,42.38) TO=c(46.7,44.2,43.1,40.9,51.9,49.3,46.2,42.38,36.3) AR=c(45,46,0.0,38.45,50.05,22.9,0,25,9) DF<-data.frame(BHID,FROM,TO,VALUE) #add the length DF$LENGTH=DF$FROM-DF$TO where: + BHID: is the borehole

Hi Everyone, I have a question regarding the construction of 3D graphs in 'R', BUT these graphs also need to illustrate movement (with time) of the prostate gland (using radiological techniques). I am not sure how to do this in 'R' although I'm sure there is some way of doing it. Below, I have copied and pasted some of the data with which I'm working on. The data

Hi all, I am trying to detect association between a covariate and a disease outcome using R. This covariate shows time-varying effect, I add a time-covariate interaction item to build Cox model as follows: COX <- coxph(as.formula("Surv(TIME,outcome)~eGFR_BASE+eGFR_BASE:TIME"),ori.data); coef exp(coef) e(coef) z p eGFR_BASE

Hi Jeff, Thank you for the suggestions -- I appreciate your help. Unfortunately, the result2 has two problems... (1) there are now 3 date columns (it looks like 2 cols are merged into 1 col) (2) the output rows should not have any of the basistime dates repeated (maybe I misstated the problem); I need the max fcst value by basistime, but also list the date value for that row; for example:

Thanks for the dput... #### reproducible example of split-apply-combine ### dta <- structure(list(date = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L), .Label = c("2012-01-25 18:00:00",

On Thu, 26 Oct 2017, Thomas Adams wrote: > Hi Jeff, > > Thank you for the suggestions -- I appreciate your help. Unfortunately, the > result2 has two problems... > > (1) there are now 3 date columns (it looks like 2 cols are merged into 1 > col) No, there are two date columns. Result2 includes the grouping value as a row name (pulled from the names of the dta2list items

Hello R-World, i am trying to calculate data for a DEM (Digital Elavation Model) which i also want to plot in R. i have the coordinates for the lower left corner which look something like this: x<-42,2 y<-50,5 besides i have the cellsize of the grid, which is: z<-1,1 what i do is to calculate the corrdinates of the cells to the right and top, what i can do by specifying the number of

In preparing data sets for the lme library, I bring the data into R, convert it to the groupedData class, which is an extension of the data.frame class, and use "dump" to create an R-readable version. To cut down on the size of these files I convert the row.names attribute from expressions like c("1", "2", ..., "54") to 1:54. I have run into a curious

Hello all! I've been struggling with is for many hours today; I'm close to getting what I want, but not close enough... I have a dataframe consisting of two date-time columns followed by two numeric columns. what I need is the max value (in the first numeric column) based on the 2nd date-time column, which is essentially a factor. But, I want the result to provide both date-time values

First, I don't have the correct lingo for this topic, so I can't really find a solution for my problem. And maybe I formulate it incorrectly, so bear with me. How would I calculate a 'constant transition matrix' if I know a given value at a given time? Let's say I know that my value is 54,0 at t=12. How do I get the initial chain value? t markov.growth 00 00.0 01 06.3

The partial R-square (or coefficient of partial determination, or squared partial correlation coefficients) measures the marginal contribution of one explanatory variable when all others are already included in multiple linear regression model. The following link has very clear explanations on partial and semi-partial correlation: http://www.psy.jhu.edu/~ashelton/courses/stats315/week2.pdf In

Dear all, For estimating Cobb-Douglad production Function [ Y = ALPHA * (L^(BETA1)) * (K^(BETA2)) ], i want to use nls function (without linearizing it). But how can i get initial values? ------------------------------------ > options(prompt=" R> " ) R> Y <- c(59.6, 63.9, 73.5, 75.6, 77.3, 82.8, 83.6, 84.9, 90.3, 80.5, 73.5, 60.3, 58.2, 64.4, 75.4, 85, 92.7, 85.4,

Dear Adrian and Ian (and r-helpers), I encountered a curious result in developing an example using the bicreg function in the BMA package: I noticed that pairs of models with equal R^2 and equal numbers of predictors had nevertheless different BIC values. Looking at the bicreg function, the definition of BIC appears to be the usual one, or close to it [bic <- n * log(1 - r2/100) + (size - 1) *

Hi all, I've written some code to generate 4 maps per screen and write the output to a jpeg. The output is fairly quick at the start (about 5 jpegs per minute) and then slows down greatly (1-2 jpegs per minute). Is there some way to speed it up? One of my thoughts is to keep the base map static on the screen and just update the points that are being plotted on the map (with the exception

Dear R list members, I'm encountering a problem with expand.model.frame(): Suppose that I define the following simple function (meant just to illustrate the problem): > fun <- function(model){ + expand.model.frame(model, all.vars(formula(model))) + } > and I have the following model, created with an explicit data argument: > mod Call:

Hi everyone! I just did some tests, and hopefully this information will help someone figure out where the problem lies. I made mp3s at 32, 40, 48, 56, 64, 80, and 96 kbps. Each of those was done at 16, 22.05, 24, 32, 44.1, and 48 khz. Everything worked for 22.5, 24, 44.2, and 48 khz. 16 khz and 32 khz did not work at 40, 48, 56, 80, and 96 kbps, but did work just fine at 32 kbps and 64 kbps.

Hi R-users,   I would like to transform my data using gamma, my data are ahll, bhall and dp1 as shown below:   > ahall      ah1  ah2  ah3  ah4  ah5  ah6  ah7  ah8  ah9 ah10 ah11 ah12 [1,] 0.9 1.01 1.24 1.85 1.85 2.45 3.67 3.02 3.06 2.33 1.86 0.96   > bhall        bh1   bh2   bh3   bh4  bh5   bh6   bh7   bh8   bh9  bh10  bh11  bh12 [1,] 48.39 44.26 37.34 29.93 33.5 26.54 20.26 25.73 20.14

Hi R-users, I'm not sure what's wrong and how do I check the error? I have 3 sets of data > aug_dt1  [1]  22.8  49.6  77.9  67.6  91.2  48.9 124.6  54.6  85.8  62.8  63.3 174.7  32.3  22.7  99.9 123.2   4.8 149.0  66.0 [20]  73.9  37.4  22.4  69.5  87.3  66.9  87.2  81.5 109.1  47.4  22.8  92.4  60.9  77.5  91.3  91.9  78.2  39.4 107.5 [39]  57.9  65.5  76.0  47.2 145.5  95.9 106.0

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