similar to: trend thresholds on time series

Hi Kevin, I think there are issues with Rui's proposed solution. For example, if there are rows in myDF1 which have a studyno which does not match any row in myDF2, then you will lose those rows. In your original request you said that you wanted to keep those rows. To demonstrate my point I need to modify your sample data. Specifically, I changed some studyno settings in myDF1, and also the

Hello, Try the following. myDF1$studyno <- as.character(myDF1$studyno) myDF2$studyno <- as.character(myDF2$studyno) i1 <- which(names(myDF1) == "pf_mcl") merge(myDF1[-i1], myDF2, by = "studyno") Hope this helps, Rui Barradas Em 13-10-2017 20:09, Kevin Wamae escreveu: > I'm trying to populate the column ?pf_mcl? in myDF1 with values from myDF2, where rows

Your example used one distinct studyno in DF1 and one distinct pf_mcl in DF2. I think that makes it hard to see what is going on, but maybe I completely misunderstand the problem. In any case, let's redefine myDF1 and myDF2. Note that myDF1 contains a studyno not in myDF2 and vice versa. myDF1 <- structure(list(studyno = c("J1000/9", "J895/7", "J931/6",

Dear @Rui Barradas, thank you for the solution. It works perfectly. On 13/10/2017, 23:35, "Rui Barradas" <ruipbarradas at sapo.pt> wrote: Hello, Try the following. myDF1$studyno <- as.character(myDF1$studyno) myDF2$studyno <- as.character(myDF2$studyno) i1 <- which(names(myDF1) == "pf_mcl") merge(myDF1[-i1], myDF2,

Dear @William<mailto:wdunlap at tibco.com>, thanks for the feedback. I have tested it on the larger dataset and noticed that it created two variables, pf_raw and pf_curated. The output we were looking for, was one that takes the variable pf_mcl in curated dataset and replaces pf_mcl in matching rows within the raw dataset. @Eric<mailto:ericjberger at gmail.com>?s solution was able to

Dear Hank, Last question first: really, only you can say for sure if 4e-281 and 5e-11 are small enough; it depends on the units you measure your state variables in. However, this strategy cannot get the state variables to exactly 0. Obviously, you could get closer to 0.0 faster by setting the derivatives even larger in absolute value. You may run into problems with the solver when the

?merge Bert On Oct 13, 2017 12:09 PM, "Kevin Wamae" <KWamae at kemri-wellcome.org> wrote: > I'm trying to populate the column ?pf_mcl? in myDF1 with values from > myDF2, where rows match based on column "studyno" but the solutions I have > found so far don't seem to be giving me the desired output. > > Below is a snapshot of the data.frames. >

I'm trying to populate the column ?pf_mcl? in myDF1 with values from myDF2, where rows match based on column "studyno" but the solutions I have found so far don't seem to be giving me the desired output. Below is a snapshot of the data.frames. myDF1 <- structure(list(studyno = c("J1000/9", "J1000/9", "J1000/9", "J1000/9",

Suppose that I have data on three species for a variable and datasets from two time periods. I want to make a boxplot of the first dataset and then add the second using 'at = ' and 'add = T' as in the example for 'boxplot.' Since the boxes are paired by species, I want to do is have the x labels be centered between the boxes. I'm doing this now with mtext and entering

Dear @Bert Gunter<mailto:bgunter.4567 at gmail.com>, I tried merge and I faced many challenges. @Rui Barradas<mailto:ruipbarradas at sapo.pt> solution is working. From: Bert Gunter <bgunter.4567 at gmail.com> Date: Friday, 13 October 2017 at 22:44 To: Kevin Wamae <KWamae at kemri-wellcome.org> Cc: R-help <R-help at r-project.org> Subject: Re: [R] Populate one data

Dear Michael, One key is adjustment of nls optimizer tolerance. I notice it has to be higher than usual, but, I recovered your noisy "known" parameter values with an error of K1 (-7%) and k1 (-6%): #### Miller problem with Dalgaard modifications ## Linares 1/22/2004 ## Solution 1 nls(noisy ~ lsoda(xstart, time, one.compartment.model, c(K1=K1, k2=k2))[,2], data=C1.lsoda,

Hi, I have a density that I need to get MLEs from, which includes definite integrals both in the denominator and in the numerator of the density function. It looks like the outcome depends on the initial values given. My program is shown below: library(circular) ######################################## 4 parameters ######################################## z<-rvonmises(100,0,1)

Hi.. i have an expression of the form: model1<-nls(y~beta1*(x1+(k1*x2)+(k1*k1*x3)+(k2*x4)+(k2*k1*x5)+(k2*k2*x6)+(k3*x7)+(k3*k4*x8)+(k3*k2*x9)+(k3*k3*x10)+ (k4*x11)+(k4*k1*x12)+(k4*k2*x13)+(k4*k3*x14)+(k4*k4*x15)+(k5*x16)+(k5*k1*x17)+(k5*k2*x18)+(k5*k3*x19)+

Hello...i want to find the empirical rate for type 1 error using fixed trimmed mean. To make it easy, i'm referring to journal given by this website http://www.academicjournals.org/ajmcsr/PDF/pdf2011/Yusof%20et%20al.pdf. I already run the programme and there is no error in it but i got zero for the empirical rate of type 1 error. The empirical rate for the type 1 error given in the journal

Thanks to Dieter Menne and Spencer Graves I started to get my way through lsoda() Now I need to use it in with nls() to assess parameters I have a go with a basic example dy/dt = K1*conc I try to assess the value of K1 from a simulated data set with a K1 close to 2. Here is (I think) the best code that I've done so far even though it crashes when I call nls()

Hi, The code below is giving me this error message: Error in while (err > eps) { : missing value where TRUE/FALSE needed In addition: Warning messages: 1: In dnbinom(x, size, prob, log) : NaNs produced 2: In dnbinom(x, size, prob, log) : NaNs produced I know from the help files that for dnbinom "Invalid size or prob will result in return value NaN, with a warning", but I am not able

Hi I want to sum over one of the dimensions of a n x k1 x k2 array in which each column is the product of the corresponding columns from two matrices with dimensions n x k1 and n x k2. I can see two approaches: a loop on k1 and a loop on k2. But I cannot figure a solution that avoids the loop? Is it possible? (I don't refer to apply or lapply etc either as they are just hidden loops so,

Hello, I haven't found errors in your code. I implemented the test in the paper (the first, fixed symetric mean) and it also gives me zero Type I errors, when alpha = 0.05. Try to see the value of min(pv) or to plot the histogram of 'pv', hist(pv) and you'll see that there are no significant p-values, at that level. Anyway I'll continue to look at it, but my first

Hi everyone! I'm matching two samples to create one sample that have pairs of observations equal for the k1 variable. Merge() doesn't work because I dont't want to recycle the values. x <- data.frame(k1=c(1,1,2,3,3,5), k2=c(20,21,22,23,24,25)) x y <- data.frame(k1=c(1,1,2,2,3,4,5,5), k2=c(10,11,12,13,14,15,16,17)) y merge(x,y,by="k1") k1 k2.x k2.y 1 1 20

Error in model.frame When I run the following nls model an error message appears and I dont know how to solve that. Could you help me?? mat = c(1,2,3,4,5,6,7,8,9,12,16,24,36,48,60) for (i in 1:length(j30)) { bliss = nls(c(j[i,1:length(mat)]) ~ b0 + b1*((1-exp(-k1*mat))/(k1*mat)) + b2*(((1-exp(-k2*mat))/(k2*mat))-exp(-k2*mat)), start = list(k1=0.1993, k2=0.1993, b0= 22.0046,