similar to: fuzzy merge

Displaying 20 results from an estimated 7000 matches similar to: "fuzzy merge"

2010 Nov 08
2
Fuzzy merge using timestamps
Greetings Supreme Council of R Masters, Like toddler, I have gotten my head stuck in the banisters of R ... again. Let it be know I am still a neophyte in the R-community forum world, so please don't flame me too bad. I have two sets of data, each with a set of timestamps. I would like to somehow merge the datasets based on the timestamps and an individual identifier. That is there are
2010 Nov 15
3
merge two dataset and replace missing by 0
Hi r users, I have two data sets (X1, X2). For example, time1<-c( 0, 8, 15, 22, 43, 64, 85, 106, 127, 148, 169, 190 ,211 ) outpue1<-c(171 ,164 ,150 ,141 ,109 , 73 , 47 ,26 ,15 ,12 ,6 ,2 ,1 ) X1<-cbind(time1,outpue1) time2<-c( 0 ,8 ,15 , 22 ,43 , 64 ,85 ,106 ,148) output2<-c( 5 ,5 ,4 ,5 ,5 ,4 ,1 ,2 , 1 ) X2<-cbind(time2,output2) I want to
2007 Jan 19
4
Newbie question: Statistical functions (e.g., mean, sd) in a "transform" statement?
Greetings listeRs - Given a data frame such as times time1 time2 time3 time4 1 70.408543 48.92378 7.399605 95.93050 2 17.231940 27.48530 82.962916 10.20619 3 20.279220 10.33575 66.209290 30.71846 4 NA 53.31993 12.398237 35.65782 5 9.295965 NA 48.929201 NA 6 63.966518 42.16304 1.777342 NA one can use "transform" to
2011 Jul 19
1
Measuring and comparing .C and .Call overhead
Further pursuing my curiosity to measure the efficiency of R/C++ interface, I conducted a simple matrix-vector multiplication test using .C and .Call functions in R. In each case, I measured the execution time in R, as well as inside the C++ function. Subtracting the two, I came up with a measure of overhead associated with each call. I assume that this overhead would be non-existent of the entire
2010 Jan 16
2
Extracing only Unique Rows based on only 1 Column
To Whomever is Interested, I have spent several days searching the web, help files, the R wiki and the archives of this mailing list for a solution to this problem, but nonetheless I apologize in advance if I have missed something obvious. The problem is this; I have a 5-column data frame with about 4.2 million rows, and want to create a new (and hopefully much smaller) data frame that
2010 Sep 02
2
date
Hello all, I've 2 strings that representing the start and end values of a date and time. For example, time1 <- c("21/04/2005","23/05/2005","11/04/2005") time2 <- c("15/07/2009", "03/06/2008", "15/10/2005") as.difftime(time1,time2) Time differences in secs [1] NA NA NA attr(,"tzone") [1] "" How can i
2007 Dec 16
4
improving a bar graph
Hello, Below is the code for a basic bar graph. I was seeking advice regarding the following: (a) For each time period there are values from 16 people. How I can change the colour value so that each person has a different colour, which recurs across each of the three graphs/tie epriods? (b) I have seen much more sophisticated examples using lattice (e.g each person has a separate
2012 Nov 30
1
help on "stacking" matrices up
Dear All,   #I have the following code   Dose<-1000 Tinf <-0.5 INTERVAL <-8 TIME8 <-matrix(c((0*INTERVAL):(1*INTERVAL))) TIME7 <-matrix(c((0*INTERVAL):(2*INTERVAL))) TIME6 <-matrix(c((0*INTERVAL):(3*INTERVAL))) TIME5 <-matrix(c((0*INTERVAL):(4*INTERVAL))) TIME4 <-matrix(c((0*INTERVAL):(5*INTERVAL))) TIME3 <-matrix(c((0*INTERVAL):(6*INTERVAL))) TIME2
2011 Sep 26
3
survival analysis: interval censored data
hello: my data looks like: time1  time2   event  catagoria 2004    2006        1            C 2004    2005        0            C 2005    2010        1            E 2007    2009        1            C 2006    2007        0            E 2008    2010        0            C 2008    2010        1            E ... and the census interval is 1 year I have tried  this
2013 Mar 21
1
All unique combinations
Dear all, I would like to have all unique combinations in the following matrix TimeIndex<- rbind (c(1,"Week_of_21_07-29_03"),           c(2,"Thursday_21_03"),           c(3,"Friday_22_03"),           c(4,"Saturday_23_03"),           c(5,"Sunday_24_03"),           c(6,"Monday_25_03"),           c(7,"Tuesday_26_03"),        
2004 Aug 05
1
Post-hoc t-tests in 2-way repeated measure ANOVA
Hi all I am running a 2-way repeated measure anova with 1 between-subjects factor (Group=treatment, control), and 1 within-subject factor (Time of measurement: time1, time2). I extract the results of the anova with: summary(aov(effect ~ Group*Time + Error=Subj/Time, data=mydata)) Now, this must be clearly a dumb question, but how can I quickly extract in R all the post-hoc t-tests for the
2011 Nov 11
1
How to compute time interval?
time1 = 2008-03-09 time2 = 2010-9-10 How to compute how many years between time1 and time2? Thanks! best [[alternative HTML version deleted]]
2009 Jan 27
2
Can I create a timeDate object using only year and week of the year values?
For a model I am working on, I have samples organized by year and week of the year. For this model, the data (year and week) comes from the basic sample data, but I require a value representing the amount of time since the sample was taken (actually, for the purpose of the model, it is sufficient to use the number of weeks from the middle of the sample week to the present). What I have found so
2007 Apr 10
1
Memory management
Hi all, I'm just curious how memory management works in R... I need to run an optimization that keeps calling the same function with a large set of parameters... so then I start to wonder if it's better if I attach the variables first vs passing them in (coz that involves a lot of copying.. ) Thus, I do this fn3 <- function(x, y, z, a, b, c){ sum(x, y, z, a, b, c) } fn4 <-
2010 May 20
1
Strange behaviour when using diff with POSIXt and POSIXlt objects
Dear list, I´m calculating time differences between series of time stamps and I noticed something odd: If I do this... > time1=strptime("2009 05 31 22 57 00",format="%Y %m %d %H %M") > time2=strptime("2009 05 31 23 07 00",format="%Y %m %d %H %M") > > diff(c(time1,time2),units="mins") Time difference of 10 mins .. I get the correct
2012 Mar 29
1
Adding duration (hh:mm:ss)\Converting factor column into duration class
Hi All, I have a data frame: Time1 Time2 1 176:46:10 41:48:06 2 171:28:57 61:19:10 3 178:25:15 34:05:35 4 74:04:20 25:01:55 5 136:11:20 37:59:32 6 138:17:17 30:22:27 7 183:04:48 29:25:02 8 179:35:01 19:29:44 > str(df) 'data.frame': 8 obs. of 2 variables: $ Time1: Factor w/ 583 levels
2008 May 09
1
predicting from coxph with pspline
Hello. I get a bit confused by the output from the predict function when used on an object from coxph in combination with p-spline, e.g. fit <- coxph(Surv(time1, time2, status)~pspline(x), Data) predict(fit, newdata=data.frame(x=1:2)) It seems like the output is somewhat independent of the x-values to predict at. For example x=1:2 gives the same result as x=21:22. Does the result span the
2004 Apr 21
1
difference between coxph and cph
Hi. I am using Windows version of R 1.8.1. Being somewhat new to survival analysis, I am trying to compare cph (Design) with coxph (survival) for use with a survival data set. I was wondering why cph and coxph provide me with different confidence intervals for the hazard ratios for one of the variables. I was wondering if I am doing something wrong? Or if the two functions are calculating hazard
2007 Dec 31
3
Survival analysis with no events in one treatment group
I'm trying to fit a Cox proportional hazards model to some hospital admission data. About 25% of the patients have had at least one admission, and of these, 40% have had two admissions within the 12 month period of the study. Each patients has had one of 4 treatments, and one of the treatment groups has had no admissions for the period. I used:
2005 Nov 15
1
Repeates Measures MANOVA for Time*Treatment Interactions
Dear R folk, First off I want to thank those of you who responded with comments for my R quick and dirty stats tutorial. They've been quite helpful, and I'm in the process of revising them. When it comes to repeated measures MANOVA, I'm in a bit of a bind, however. I'm beginning to see that all of the documentation is written for psychologists, who have a slightly