similar to: Interpolation Problems

Dear all, I have run into a problem when running some code implemented in the Bioconductor panp-package (applied to my own expression data), whereby gene expression values of known true negative probesets (x) are interpolated onto present/absent p-values (y) between 0 and 1 using the *approxfun - function*{stats}; when I have used R version 2.8, everything had worked fine, however, after updating

Is it possible to interpolate a value for x with knowledge of y? For example, approx(x, y, xout) will give me y's given a set of x's, which is opposite to what I'm after. I've tried switching x and y, e.g., approx(y, x, xout), but in a real data set it is possible to have more than one y for a given x causing approx() to remove coordinates. Thanks for your help, Greg.

Readers, According to the help '?approxfun', the function can be used to obtain the interpolated values. The following test was tried: > testinterpolation<-read.csv('test.csv',header=FALSE) > testinterpolation V1 V2 1 10 2 2 20 NA 3 30 5 4 40 7 5 50 NA 6 60 NA 7 70 2 8 80 6 9 90 9 10 100 NA >

Readers, I have looked at various documents hosted on the web site; I couldn't find anything on interpolation. So I started r and accessed the help (help.start()). (by the way is it possible to configure r to open help in opera instead of firefox?) Initially I read the help for the akima package but couldn't understand it. Next I tried the asplines package help. I tried to copy the

Hi people, I am new in this list and could not find a FAQ for it in particular, furthermore I could not find my question answered in the official R FAQ or docs. I have simply something like this: > f<-approxfun(data[,1],data[,2]) and f is: > f function (v) .C("R_approx", as.double(x), as.double(y), as.integer(n), xout = as.double(v), as.integer(length(v)),

Below is the code that I am using in a much larger function. I would expect a bankfull measure at zero to be between 0.6 and 0.8 approxfun is returning 0.8136986. I am sure that I am missing something. measure_bkf <- (structure(list(measurment_num = c(0, 0.2, 0.4, 0.6, 0.8, 1, 1.2, 1.4, 1.6, 1.8, 2, 2.2, 2.4, 2.6, 2.8, 3, 3.2, 3.4), bankfull_depths_m = c(-0.48, -0.48, -0.42, -0.26, 0.58,

Hello R Users, How to make a variable equidistance with time i.e. how to interpolate a variable if it is not sampled at equal time interval. Many thanks, Regards, Yogesh [[alternative HTML version deleted]]

Dear all; First of all, this is probably a more conceptual question than a R-related one, but still want to give it a try. When working with the interpolation function "interp" from the package akima and the triangulation function "tri.mesh" from package tripack I've got NA's for the interpolation and "error" for the triangulation. The data is arranged in a

Hi, I have three matrices (X,Y,P) with the same dimension. The X,Y grid is regular and I want to perform linear interpolation to pick out certain points. In matlab appropriate call is something like Pout=interp2(X,Y,P,Xout,Yout, method="linear") where Xout and Yout are the locations where I want the Pout data (typically a different grid). (Scipy has this routine in

Full_Name: joerg van den hoff Version: 1.9.1 OS: MacOS and SunOS Submission from: (NULL) (149.220.4.88) follow up to ID 7166. something like approx(c(1,2),c(NA,NA),1.5,rule=2) crashes 1.9.1 on both systems (MacOS 10.3.5.: bus error, SunOS 5.9: segmentation fault) even if xout is within given x range (as in example above) where rule=2 seems not be relevant anyway.

Dear all, I'm having trouble interpolating a number of gridded datasets that I have. I'm quite new to R so any help/advice that can be offered would be much appreciated! Firstly I'll describe my dataset. The data is a grid of the planet at 1 degree spatial resolution, with each grid cell containing a value describing a particular variable (e.g. population density) for coordinate

hi guys I need to interpolate values for the zero coupon yield curve. Following data is given date days rate 1996 01

I am working on a project where we start with start with 2 long, equal-length vectors, massage them in various ways, and end up with a function mapping one interval to another. I'll call that function "f1." The last step in R is to generate f1 as the value of the approxfun function. I would like to put f1 into a package, but without having the package redo the creation of

Readers, Am trying to use the function 'approx' to interpolate time series data sets: data1: 01:23:40 5 01:23:45 10 01:23:50 12 01:23:55 7 data2: 01:23:42 01:23:47 01:23:51 01:23:54 The objective is to obtain interpolated values of 'data1' column 2 (5, 10, 12, 7) for the times shown in data2. Tried the following command but received the error shown:

I have a huge data set in the form of            V1           V2         V3   V4     V5  V6 1     201005010000201005010000 1.68291.38 1  0 2     201005010000201005010300 0.93335.10 1  0 3     201005010000201005010600 2.25 57.38 1  0 4     201005010000201005010900 0.43 13.76 1  0 5     201005010000201005011200 0.74101.14 1  0 I am interested in interpolating it on an hour basis(it's for avery

I'm testing R version 2.7.0 on windows and there seems to be a compatibility issue with objects that were created by "approxfun" in older versions. As long as the objects were created in version 2.7.0 things work ok, but calling the interpolated functions from R version 2.0.1 causes this error: Error in .C("R_approx", as.double(x), as.double(y), as.integer(n), xout =

>>>>> Robert Almgren >>>>> on Fri, 3 May 2019 15:45:44 -0400 writes [ __ to R-help __ -- here diverted to R-devel on purpose] > There is something I do not think is right in the approx() > function in base R, with method="constant" and in the > presence of NA values. I have 3.6.0, but the behavior > seems to be the same in

Hello again, There is any package which does Z aware (real 3D) interpolations? It can be any method (IDW, kriging or spline) but it should take into consideration not only x and y coordinates for interpolation, but also z coordinate. I looked into different packages but it seems i didn't find the right one. The ultimate goal is to import the output into a GIS (Geographical Information

Greetings, How might one go about generating a smooth interpolation of a survival curve generated by the survfit function in the survival package? I am able to package my variables by standard methods >x<-(survfit(Surv(time),data) and plot the "step" curve, but would like to obtain a smooth estimation curve for the purpose of approximating survival time between steps on the

Dear R forum I have data.frame as df = data.frame(rate_name = c("USD_1w", "USD_1w", "USD_1w", "USD_1w", "USD_1m", "USD_1m", "USD_1m", "USD_1m", "USD_2m", "USD_2m", "USD_2m", "USD_2m",  "GBP_1w", "GBP_1w", "GBP_1w", "GBP_1w",