similar to: Models

Hi all, I have a data set with time interval and depending on the interval I want to create 5 more variables . Sample data below obs, Start, End 1,2/1/2015, 1/1/2017 2,4/11/2010, 1/1/2011 3,1/4/2006, 5/3/2007 4,10/1/2007, 1/1/2008 5,6/1/2011, 1/1/2012 6,10/15/2004,12/1/2004 First, I want get interval between the start date and end dates (End-start). obs, Start , end, datediff

Ii is difficult to provide useful help, because you have failed to read and follow the posting guide. In particular: 1. Plain text, not HTML. 2. Use dput() or provide code to create your example. Text printouts such as that which you gave require some work to wrangle into into an example that we can test. Specifically: 3. Have you gone through any R tutorials?-- it sure doesn't look like

Hello. I'd like to compute the associate vector of distances between leaves in a binary non-rooted tree. The definition of a distance between two leaves in a binary non-rooted tree is the number of edges in the path joining the two leaves. I've tried the ape package but I'm unable to find this vector. For example, using rtree(5,rooted=F) I've obtained the following tree: $edge

# read.table is NOT part of the data.table package #library(data.table) DFM <- read.table( text= 'obs start end 1 2/1/2015 1/1/2017 2 4/11/2010 1/1/2011 3 1/4/2006 5/3/2007 4 10/1/2007 1/1/2008 5 6/1/2011 1/1/2012 6 10/5/2004 12/1/2004 ',header = TRUE, stringsAsFactors = FALSE) # cleaner way to compute D DFM$start <- as.Date( DFM$start, format="%m/%d/%Y" ) DFM$end

Thank you all for the useful suggestion. I did some of my homework. library(data.table) DFM <- read.table(header=TRUE, text='obs start end 1 2/1/2015 1/1/2017 2 4/11/2010 1/1/2011 3 1/4/2006 5/3/2007 4 10/1/2007 1/1/2008 5 6/1/2011 1/1/2012 6 10/5/2004 12/1/2004',stringsAsFactors = FALSE) DFM DFM$D =as.numeric(difftime(as.Date(DFM$end,format="%m/%d/%Y"),

Since the number of choices is small (6), how about this? Starting with Jeff's initial DFM: DFM <- structure(list(obs = 1:6, start = structure(c(16467, 14710, 13152, 13787, 15126, 12696), class = "Date"), end = structure(c(17167, 14975, 13636, 13879, 15340, 12753), class = "Date"), D = c(700, 265, 484, 92, 214, 57), bin = structure(c(6L, 3L, 5L, 1L, 3L, 1L), .Label

Thank you Jeff and All, Within a given time period (say 700 days, from the start day), I am expecting measurements taken at each time interval;. In this case "0" means measurement taken, "1" not taken (stopped or opted out and " -1" don't consider that time period for that individual. This will be compared with the actual measurements taken (Observed-

The data set consists of two sets of matrices, as labelled by the columns, T's and C's. > xy x T1 T2 T3 T4 T5 C1 C2 C3 C4 C5 [1,] 50 0.00 0.00 33.75 0.00 0.00 0.00 36.76 0.00 35.26 0.00 [2,] 13 34.41 0.00 0.00 36.64 32.86 34.11 35.80 37.74 0.00 0.00 [3,] 14 35.85 0.00 33.88 36.68 34.88 34.58 0.00 32.75 37.45 0.00 [4,] 33 34.56

Hello, In R I am trying to use Kalman filtering to find a solution for an hydrological problem. With Kalman Filtering I want to estimate the discharge comming from three storage bassins. I have programmed a function in R which can run KalmanSmooth. When I'm asking for the function and putting in values, R detects the following error: "Error in as.vector(data) : Argument "S1" is

dear list: I need help to achieve a simpler code to complete a task I'm performing. here is an example: dat<-expand.grid(a=seq(1,5),b=seq(1000,1005)) I want to add a new column dat$c in that: t1<-ifelse(dat$a==1&dat$b==1001,1001,0) t2<-ifelse(dat$a==2&dat$b==1002,1001,0) t3<-ifelse(dat$a==3&dat$b==1003,1001,0) t4<-ifelse(dat$a==1&dat$b==1002,1002,0)

Hello all. I wish to read a large data set into R. My current issue is in getting the data so that R would be able to access it. Using read.table won't work since the data is over 1GB in size (and I am using windows XP), so my plan was to read the file chunk by chunk and each time move it into bigmemory (I'll play with that when the time will come, maybe ff is better ?!). I encountered

Hi, Yes, ldd is generating wrong tbss size. It is just considering one tbss section and not calculating all sections from all objects. The following example on x86_64 shows the issue: --- t0.c --- #include <stdio.h> extern __thread int t0; extern __thread int t1; extern __thread int t2; extern __thread int t3; __thread int t4; __thread int t5; __thread int t6; __thread int t7; int

Hi, I'm running a calculation in two ways. The first way is to employ vectors and evaluate a function in one go. The second way is to break down the function into pieces and combine the pieces to the final answer. Algebraically, they should give me the same result. But the final vector differs significantly. I must be missing something very obvious, but I just cannot see it xx <-

Hi! I have a difficulty in the use of function optimize(). Could you help me? I want to maximize this function: ##### Logaritmo da distribui??o condicional de alpha[i] lp_alphai <- function(alphai, i, beta, tau, N){ t1 <- (N[i+1] - N[i])*log(alphai) t2 <- - (N[i+1] - N[i])*alphai*log(beta[i]) t3 <- (alphai - 1)*sum(log(times[(N[i] + 1):N[i+1]])) t4 <- -

Dear R-users, actually i try to parse some state protocols for my work. i an easy stetting the code below works fine, if states are reached only once. in harder settings it could be possible that one state gets visited more times. in this case for me its interesting to see how much waiting time lies between to states on the whole. by the way i didn't use R as a parsing tool so far, so

Hallo! I have two groups (placebo/verum), every subject is measured at 5 times, the first time t0 is the baseline measurement, t1 to t4 are the measurements after applying the medication (placebo or verum). The question is, if there is a significant difference in the two groups and how large the differnce is (95% confidence intervals). Let me give sample data # Data

hello, I have a simple question: I want to compute the average of 6 variables, my data looks like this: t0 t1 t2 t3 t4 t5 1 32 34 36 40 38 40 2 35 37 38 36 33 39 . . . I want the mean of t0-t5 for each row (observation). thank you, sigalit. [[alternative HTML version deleted]]

Hi, I have big .csv file. I would like to filter that file into a new table. For example, I have .csv file as below: f1 f2 f3 f4 f5 f6 f7 f9 f10 f11 t1 1 0 1 0 1 0 0 0 0 1 t2 1 0 0 0 0 1 1 1 1 1 t3 0 0 0 0 0 0 0 0 0 0 t4 1 0 0 0 1 0 0 0 0 0 t5 0 0 0 0 0 0 0 0 0 0 t6 0 0 0 0 0 0 0 0 0 0

Hi, I need some help on integrating a function that is a vector. I have a function - vector which each element is different. And, naturally, function integrate() does not work I checked the article of U. Ligges and J. Fox (2008) about code optimization "How Can I Avoid This Loop or Make It Faster?" on http://promberger.info/files/rnews-vectorvsloops2008.pdf. Their advice did not help

I have big .csv file. I would like to filter that file into a new table. For example, I have .csv file as below: f1 f2 f3 f4 f5 f6 f7 f9 f10 f11 t1 1 0 1 0 1 0 0 0 0 1 t2 1 0 0 0 0 1 1 1 1 1 t3 0 0 0 0 0 0 0 0 0 0 t4 1 0 0 0 1 0 0 0 0 0 t5 0 0 0 0 0 0 0 0 0 0 t6 0 0 0 0 0 0