search for: extrapolation

Dear list members, When I create a simple scatterplot with a regression line (se below) the line is automatically extrapolated outside the range of data points. Why is this and how can I prevent R from extrapolating the regression line? Thank you in advance, Johan model<-lm(Herb~Para) plot(Para,Herb) abline(model)

Dear R-Experts, Here below my R code working but I don't know how to complete/finish my R code to get the final plot with the extrapolation for the10 more years. Indeed, I try to extrapolate my data with a linear fit over the next 10 years. So I create a date sequence for the next 10 years and store as a dataframe to make the prediction possible. Now, I am trying to get the plot with the actual data (from year 2004 to 2018) and with t...

Hi, I am facing a problem in extrapolation of data series. It is a series of Bond yields, I am having the yield for 1 year to 30 years. I want to find the yield for 0.5 year and 30.5 years. I used the Langrange's Extrapolation but the extrapolation deviates from the normal trend ( as we can see in theoritical yield curves) very sharply,...

Hi, We have an experiment where individuals responses were measured over 5 days. Some responses were not obtained because we only allowed individuals to respond within a limited time-frame. These individuals are given the maximum response time as they did not respond, yet we feel they may have done if given time (and by looking at the rest of their responses over time, the non-response days stand

Dear all I generated predicted risk of death for each subject in the study by means of Cox proportional hazards model at 8 year of follow-up, a time point at which follow-up was more than 90% complete. It is possible to extrapolate to 10-year the predicted risk of each subjet by assuming an exponential distribution? Any help would be greatly appreciated. Thanks for your consideration.

...expecting to see in the file dataimportextra.csv something like: 1,1990 2,1991 3,1993 ... to previously known data 10,2000 ... final extrapolated value, e.g. 20,2010 I didn't ; this suggests that I chose the wrong function! Can someone please advise me of the correct function to use for this extrapolation task? yours, r251 mandriva2009

Hi all, I'm fitting a line to my dataset. Later I want to predict missing values that exceed the [min,max] interval of my empirical data, therefore I choose surface="direct" for extrapolation. l1<-loess(y1~x1,span=0.1,data.frame(x=x1,y=y1),control=loess.control(surface="direct")) In my application it is highly important that the fitted line intercepts at the point of origin. Is it possible to do this in R? Thanks in advance. Cheers, Torsten --

Dear R-experts, I write to you to know if somebody is aware of a R package (or function) able to plot graphs for extrapolation. I need to be clear on what extrapolation really is to me. It is when we use the model for X variables outside the range of X variables that were used to construct the model and estimates.? What I am really looking for is that beyond confidence intervals for predictions for the one estimated mode...

...late the model out to 3 years? Are there functions that are equivalent to the 'pweibull' function for all these distributions? Any help you could give on this would be most appreciated. Kind regards, Tim. -- View this message in context: http://r.789695.n4.nabble.com/Survival-analysis-extrapolation-tp2231735p2231735.html Sent from the R help mailing list archive at Nabble.com.

Dear R-help, I have fitted a glm logistic function to dichotomous forced choices responses varying according to time interval between two stimulus. x values are time separation in miliseconds, and the y values are proportion responses for one of the stimulus. Now I am trying to extrapolate x values for the y value (proportion) at .25, .5, and .75. I have tried several predict parameters, and they

Hi, I have been trying to do numerical differentiation using R. I found some old S code using Richardson Extrapolation which I managed to get to work. I am posting it here in case anyone needs it. ######################################################################## richardson.grad <- function(func, x, d=0.01, eps=1e-4, r=6, show=F){ # This function calculates a numerical approximation of the first # der...

Dear?R experts, ? I?am trying to do linear extrapolation on a dataset?like the attached document. I looked at the approx and approxfun function that seem to do this function, but not fully understand them. I was wondering if someone could help with writing commands to do the following based on the attached file's example: ? ID#1 and ID?#2 both have r...

...in order to have a full coverage of the species diversity in my sample. Is there anyone who knows how to do this? Using vegan or any other package? Or is there any other way to calculate this x-value? Thanks in advance! Guillaume -- View this message in context: http://r.789695.n4.nabble.com/Extrapolation-of-rarefaction-curve-tp4693693.html Sent from the R help mailing list archive at Nabble.com.

> Hello, Hi :) First off, could you try to set your email client to break long lines before transmitting? In my (somewhat outdated) pine, the lines appear as VERY long lines when I try to reply, making it hard to read :) Minor detail though, I should probably fix pine. Some day. > The way you describe how the jitter buffer should be implemented makes me > wonder: How does the

...he resources (again, an empirical rule dictates the computation time and memory usage). I'm looking for advice on this second point (both on the technical aspect, and whether this is sound statistically): - I can foresee that I should always start with a few y values before I can do any extrapolation, but how many of them? 3, 10? How could I know? - once I have enough points (say, 10) to use the fitting procedure and get an estimate of the error, how should I decide the best location of the next y if the error is too important? - in a practical implementation, I would use a while loop a...

Dear R users, i try to integrate lgamma from 0 to Inf. But here i get the message "roundoff error is detected in the extrapolation table", if i use 1.0e120 instead of Inf the computation works, but this is against the suggestion of integrates help information to use Inf explicitly. Using stirlings approximation doesnt bring the solution too. ## Stirlings approximation lgammaApprox <- function(x) { 0.5*log(2*pi)+(x-(...

I am using a multiple additive model (in the quantreg package) and I would like to 'extract' the fitted model formulae ie- for a straight line the formula would be y= 'a+b*c' for my multiple model I would expect somthing more complex because the model is not linear (its a bit like a GAM) but given I can plot the model using # f<-fitted(model) #lines(f) there must be a formula

Hello, I'd like to generate some reports on users log in and log out times, is there a way to do this with/without using smbd log files? I was looking at the log files and it looks like I can determine the time of login by looking for : [2006/02/10 09:31:46, 3] libsmb/ntlmssp.c:ntlmssp_server_auth(615) Got user=[jsmith] domain=[CORP] workstation=[DHCP31247] len1=24 len2=24

I've already fixed the bugs, but as with the last one, this is not critical enough to allow breaking current R-devel's code freeze. I hope I will have corrected it for 1.5.1.. ## Here is code reproducing the problems; ## I use try(.) whenever I know the current versions of R would ## give an error: library(splines) x <- c(1:3,5:6) y <- c(3:1,5:6) (isP <- interpSpline(x,y))#

Dear R experts: I need to get this plot, but also with 95% confidence interval bands: hour <- c(1, 2, 3, 4, 5, 6) millivolts <- c(3.5, 5, 7.5, 13, 40, 58) plot(hour, millivolts, xlim=c(1,10), ylim=c(0,1000)) pm <- lm(millivolts ~ poly(hour, 3)) curve(predict(pm, data.frame(hour=x)), add=TRUE) How can the 95% confidence interval band curves be plotted too? Sincerely,