search for: locpoly

...kage installed, please uncomment below line. # install.packages("KernSmooth") library(KernSmooth) rst <- data.frame(hsp = rnorm(23), dal = rnorm(23) gs <- 350 ts <- seq(1, 353, 16) bw <- lapply(rst, dpill, x = ts, gridsize = gs) # If I just want to apply locpoly function seperately lp.hsp <- locpoly(x = ts, y = rst$hsp, bandwidth = bw$hsp, gridsize = gs) lp.dal <- locpoly(x = ts, y = rst$dal, bandwidth = bw$dal, gridsize = gs) -------------------------------------------------------------------------------------------- In above example, I can apply t...

is there a way of estimating derivative curves, similar to the ones we get from 'locpoly', from 'loess' estimation. i am interested in estimation of 1st and 2nd derivatives... --------------------------------- [[alternate HTML version deleted]]

Dear R Users, When using locpoly function, number of output values is smaller than the number of input values. How is it possible to get number of output component $y equal to the number of inputs. Thanks a lot, Amir --------------------------------- [[alternative HTML version deleted]]

Dear list, I've got a question concerning difference between loess and locpoly. I have to use a plug-in method to chose a bandwith so I take locpoly method to fit a curve. My problem is:I know how to get predicted values in loess: m=loess(y~x) y_fitted=predict(m). But how to get the same in locpoly? I computed like this: bw=dpill(x, y, blockmax = 5, divisor = 20,trim =...

1. Please do make use of the subject line. 2. Please (re-)read the description of the `range.x' argument in ?locpoly: it's suppose to be a vector of min and max x values. 3. I hope you realize how grossly inefficient this computation is... Andy > From: klea lambrou > > > hello R-users.could you please help me on this one?i have > 2 vectors x1 > and y1 and both have the same size...

Hello All, Is there a local bandwidth selection routine for local polynomial regression (locpoly) ? Thanks Chinthaka Kuruwita

Dear R users, I am currently using the locpoly function from the KernSmooth package to estimate densities. However, I have some trouble understanding how this estimation technique is implemented in R. My main concern comes from the fact that this function gives negative estimates when the bandwidth is sufficiently large (mainly in the tails of...

Hi Does R have a function or has someone written a function to draw a 3d surface from a scatter plot of values using either ksmooth or locpoly. OR a transform function a that merges x relation z and y relation z to (x,y) relation z? I tried out scatterplot3d but it seems it would take a bit of work to get scatterplot3d to draw a curved surface. Lawrence

...nd dpill in the kernsmooth library , the purpose is to incorporate other selection criterion for the bandwidth in which a varying bandwidths are replaced instead of the constant bandwidth. I will send you back the improved version as soon as I get the fortran code for the upper mention functions. ((LOCPOLY and DPILL ))) -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-re...

Hi: I am using the package "KernSmooth" to do the local polynomial regression. However, it seems the function "locpoly" can only deal with univariate covaraite. I wonder is there any kernel smoothing package in R can deal with bivariate covariates? I also checked the package "lcofit" in which function "lcofit" can indeed deal with bivariate case. The code below is an example from the its he...

...cp.o g77 -mieee-fp -fPIC -g -O2 -c dgedi.f -o dgedi.o g77 -mieee-fp -fPIC -g -O2 -c dgefa.f -o dgefa.o g77 -mieee-fp -fPIC -g -O2 -c dgesl.f -o dgesl.o g77 -mieee-fp -fPIC -g -O2 -c linbin2D.f -o linbin2D.o g77 -mieee-fp -fPIC -g -O2 -c linbin.f -o linbin.o g77 -mieee-fp -fPIC -g -O2 -c locpoly.f -o locpoly.o g77 -mieee-fp -fPIC -g -O2 -c rlbin.f -o rlbin.o g77 -mieee-fp -fPIC -g -O2 -c sdiag.f -o sdiag.o g77 -mieee-fp -fPIC -g -O2 -c sstdiag.f -o sstdiag.o gcc -shared -o KernSmooth.so blkest.o cp.o dgedi.o dgefa.o dgesl.o linbin2D.o linbin.o locpoly.o rlbin.o sdiag.o sstdiag.o -lf...

...function (v) .C("R_approx", as.double(x), as.double(y), as.integer(n), xout = as.double(v), as.integer(length(v)), as.integer(method), as.double(yleft), as.double(yright), as.double(f), NAOK = TRUE, PACKAGE = "base")$xout <environment: 02106C24> I also used "locPoly". Both yield either a function or a data frame of values. Is there a way to get a mathematical representation of the function, e.g. a polynomial of any order? Something like ax^3+bx^2+cx^1+d or similar if it is of degree 3? Basically, I want to create functions of measured values. Thanks...

hello R-users.could you please help me on this one?i have 2 vectors x1 and y1 and both have the same size.i want to use the locpoly function from the kernsmooth package in order to estimate a regression function.at each estimation i want to leave one observation out,and i want my estimation to be at the observation i left out.i tried : for (j in 1:length(x1)) + A<-locpoly(x1[-1],y1[-1],bandwidth=4,gridsize=1...

...s of the polynomial to be evaluated). <http://www.mathworks.com/access/helpdesk/help/techdoc/ref/polyval.html> I have possibly missed it in the R help files, so please excuse me if I have. "Polynomial evaluation" yielded no result in a search of help, and the functions poly() and locpoly() don't seem to be what I am after. > Sam > ---- > Sam McClatchie, > Sub-program leader, Pelagic Fisheries > South Australian Aquatic Sciences Centre > PO Box 120, Henley Beach 5022 > Adelaide, South Australia > email <mcclatchie.sam at saugov.sa.gov.au> > Tele...

...ypes of kernel regression estimators and corresponding R functions. While comparing different functions I noticed that stats::ksmooth returned different estimates for the same bandwidth as other kernel regression estimators that should be equivalent (i.e. the local polynomial estimators KernSmooth::locpoly and locpol::locpol with degree 0). However, when optimizing the bandwidth of ksmooth separately using the same loss function, I find comparable estimates to the other two estimators for a (larger) different bandwidth. To confirm this, I wrote my own Nadaraya-Watson kernel regression estimator, whic...

...rnel regression estimators and corresponding R functions. > While comparing different functions I noticed that stats::ksmooth returned different estimates for the same bandwidth > as other kernel regression estimators that should be equivalent (i.e. the local polynomial estimators KernSmooth::locpoly and > locpol::locpol with degree 0). However, when optimizing the bandwidth of ksmooth separately using the same loss function, I find comparable estimates to the other two estimators for a (larger) different bandwidth. To confirm this, I wrote my own Nadaraya-Watson kernel regression estimator,...

...on CRAN Update (y/N)? y [snip] Installing *source* package `KernSmooth' ... [snip] cc -I/sw/lib/R/include -I/sw/include -fno-common -g -O2 -c sstdiag.c -o sstdiag.o cc -bundle -bundle_loader /sw/lib/R/bin/R.bin -o KernSmooth.so blkest.o cp.o dgedi.o dgefa.o dgesl.o linbin.o linbin2D.o locpoly.o rlbin.o sdiag.o sstdiag.o -lf77blas -lcblas -latlas -L/usr/local/lib -lf2c -lm /usr/bin/ld: can't locate file for: -lf77blas make: *** [KernSmooth.so] Error 1 ERROR: compilation failed for package `KernSmooth' Installing *source* package `cluster' ... [snip] cc -bundle -bundle_loade...

...he polynomial to be evaluated). > <http://www.mathworks.com/access/helpdesk/help/techdoc/ref/pol yval.html> I have possibly missed it in the R help files, so please excuse me if I have. "Polynomial evaluation" yielded no result in a search of help, and the functions poly() and locpoly() don't seem to be what I am after. > Sam > ---- > Sam McClatchie, > Sub-program leader, Pelagic Fisheries > South Australian Aquatic Sciences Centre > PO Box 120, Henley Beach 5022 > Adelaide, South Australia > email <mcclatchie.sam at saugov.sa.gov.au> > Tele...

Hallo R-users, I would like to know if there is a way to get the effective degrees of freedom in local polinomial regression. At the moment, to carry out the local polinomial regression, I am using the function locpoly() in library KernSmooth (I need to estimate both the regression function and its derivatives, up to the 3rd one). Thanks, Simone -- Simone Vantini MOX - Modeling and Scientific Computing Dipartimento di Matematica "F. Brioschi" Politecnico di Milano Piazza Leonardo da Vinci, 32 I-201...

Hi, R users   I need to use the function (locpoly) to fit a local poynomial regression model, The defult for kernal function is " normal" , but  I need to use different kernal functions such as :Uniform,Triangular,Epanechnikov,...... Could someone help me define these functions to fit local polynomial regression model?. Email:assaedi76@y...