search for: hmin

...ot;week") setkeyv(temp_hist, mykey) setkeyv(humid_hist, mykey) # hist<- merge(temp_hist, humid_hist, by=mykey) # hist$X.x <- NULL hist$X.y <- NULL # # Max hist_max <- hist hist_max$FIPS <- hist_max$year <- hist_max$month <- hist_max$tmin <- hist_max$tmean <- hist_max$hmin <- hist_max$hmean <- NULL # # Adding Factors hist_max$citycode <- rep(101,nrow(hist_max)) hist_max$year <- rep(2010,nrow(hist_max)) hist_max$lnincome <- rep(10.262,nrow(hist_max)) # # Predictions pred_hist_max <- predict.gam(gam_max_count_wk,hist_max) # pred_hist_max <- as.data...

...C 970 (2.2) Number Of CPUs: 2 CPU Speed: 2 GHz L2 Cache (per CPU): 512 KB Memory: 1.5 GB Bus Speed: 1 GHz Boot ROM Version: 5.0.7f0 Serial Number: XB3472Q1NVS My Error Message > system.time( + outAc2 <- as.data.frame(lsoda(xstart,times, pondamph, parms, tcrit=170*730, hmin=.1)) + ) [1] 0.02 0.01 0.04 0.00 0.00 Warning messages: 1: lsoda-- at t (=r1) and step size h (=r2), the 2: corrector convergence failed repeatedly 3: or with abs(h) = hmin 4: Returning early from lsoda. Results are accurate, as far as they go Thanks for any input. Hank Stevens D...

...were differernt, are there any problem with the codes that i used? What does these warnings mean? Q2: As we know, the span is an important role for smoothing, so i try to choose the optimal span by the AIC criterion. But it seemed that i can't run it successfully, My codes are listed below. hmin<-0.05; hmax<-0.95; hstart<-hmin; nh<-100 hstep<-(hmax-hmin)/(nh-1) aic.h<- matrix(NA,nrow=nh,ncol=2) for (i in 1:nh) { htry<-hstart+(i-1)*hstep m.gam <-gam(mark~lo(x,y,span=htry)+lo(lstday2004,span=htry)+lo(slope,span=htry)+lo(ndvi2004,span=htry)+lo(elevation,span=htry...

...- 360 min and calculate on each minute. In order to reduce computing time, I want to calculate for every two minutes, but I don't know how to do it. I try to make t to be t <- seq(0, 360, by = 2), however, the computing time is still about 6 sec instead of 3. I also found that there is a hmin parameter in odesolve. But again, it doesn't work. The second question is that I found that some time, the last two or three points of calculation is NA. Thanks. Guan [[alternative HTML version deleted]]

...zone=32 +ellps=WGS84") colnames(mysamplexy) <- c ("xCord", "yCord") ID <- mysample$ID datltraj <- as.ltraj(mysamplexy, mysampletime, id=ID) Ddat <- BRB.D(datltraj, Tmax=21600, Lmin=36) BRBdat <- BRB(datltraj, D= Ddat,type=c("UD"),Tmax=21600,Lmin=36, hmin=100) kernel.area(BRBdat, unout=c("km2")) # unfortunately my data are not a very good example. Sorry about that. But I guess you know what I mean. # Because I wish to run the functions three times I do want a data frame (or matrix) in the end, which includes the results (kernel areas):...

Good afternoon, After cuting a hierarchical tree using cutree(), how to check correspondances between classes and branches? This is what we do: srndpchc <- hclust(dist(srndpc$x[1:1000,1:3]),method="ward") #creation of hierarchical tree plclust(srndpchc,hmin=20000) #visualisation srndpchc20000 = cutree(srndpchc,h=20000) #returns 4 classes table(srndpchc20000 ) srndclass20000 = cbind(srnd@data[1:1000,],srndpchc20000) #assigning classes to objects srndcents20000 <- aggregate(srndclass20000, by=list(srndpchc20000), FUN=median) matplot(1:36,t(srndcent...

...if (!is.null(boundary)) { sor2 <- adehabitatHR:::.fbboun(sor2, boundary, sigg, max(so$h)) } sor2 <- new("estUD", sor2) slot(sor2, "h") <- list(values = list(hmin=hmin, D=D), interp = so, meth = "BRB-specified") slot(sor2, "vol") <- FALSE return(sor2) [[alternative HTML version deleted]]

...) colnames( mysamplexy ) <- c( "xCord", "yCord" ) datltraj <- as.ltraj( mysamplexy, mysample$mysampletime, id=mysample$ID ) Ddat <- BRB.D( datltraj, Tmax=21600, Lmin=36 ) BRBdat <- BRB( datltraj, D = Ddat, type = "UD", Tmax = 21600, Lmin = 36, hmin = 100 ) result[ , i ] <- kernel.area( BRBdat, unout = "km2" ) } #> Warning in kernel.area(BRBdat, unout = "km2"): The grid is too small to allow the estimation of home-range #> for the following value of percent: 70,75,80,85,90,95. You should rerun kernelUD with a la...

Hello, I wanted to test the odesolve package and tried to use compiled C-code. But when I do: erg <- lsoda(y, times, "mond", parms, rtol, atol, tcrit=NULL, jacfunc=NULL, verbose=FALSE, dllname="mond", hmin=0, hmax=Inf) I get the error message: Error in lsoda(y, times, "mond", parms, rtol, atol, tcrit = NULL, jacfunc = NULL, : Unable to find mond in mond The C code is: #include <math.h> void mond(long int *neq, double *t, double *y, double *ydot)...

...;) > colnames(mysamplexy) <- c ("xCord", "yCord") > ID <- mysample$ID > datltraj <- as.ltraj(mysamplexy, mysampletime, id=ID) > Ddat <- BRB.D(datltraj, Tmax=21600, Lmin=36) > BRBdat <- BRB(datltraj, D= Ddat,type=c("UD"),Tmax=21600,Lmin=36, hmin=100) > kernel.area(BRBdat, unout=c("km2")) > > # unfortunately my data are not a very good example. Sorry about that. But > I guess you know what I mean. > > # Because I wish to run the functions three times I do want a data frame > (or matrix) in the end, which inclu...

...daspk(y = yini, dy = dyini, times = times, res = Res_DAE, parms = pars, atol = 1e-10, rtol = 1e-10) ERROR: daspk-- warning.. At T(=R1) and stepsize H (=R2) the nonlinear solver f nonlinear solver failed to converge repeatedly of with abs (H) = H repeatedly of with abs (H) = HMIN preconditioner had repeated failur 0.0000000000000D+00 0.5960464477539D-14 Warning messages: 1: In daspk(y = yini, dy = dyini, times = times, res = Res_DAE, parms = pars, : repeated convergence test failures on a step - inaccurate Jacobian or precond...

...daspk(y = yini, dy = dyini, times = times, res = Res_DAE, parms = pars, atol = 1e-10, rtol = 1e-10) ERROR: daspk-- warning.. At T(=R1) and stepsize H (=R2) the nonlinear solver f nonlinear solver failed to converge repeatedly of with abs (H) = H repeatedly of with abs (H) = HMIN preconditioner had repeated failur 0.0000000000000D+00 0.5960464477539D-14 Warning messages: 1: In daspk(y = yini, dy = dyini, times = times, res = Res_DAE, parms = pars, : repeated convergence test failures on a step - inaccurate Jacobian or preconditioner? 2: In daspk(y = yini,...

I'm solving the differential equation dy/dx = xy-1 with y(0) = sqrt(pi/2). This can be used in computing the tail of the normal distribution. (The actual solution is y(x) = exp(x^2/2) * Integral_x_inf {exp(-t^2/2) dt} = Integral_0_inf {exp (-xt - t^2/2) dt}. For large x, y ~ 1/x, starting around x~2.) I'm testing both lsoda and rk4 from the package odesolve. rk4 is accurate using step

...age is based on S4 methods and classes. o Changes in package 'mva': - factanal() now returns the test statistic and P-value formerly computed in the print method. - heatmap() has many more arguments, partly thanks to Wolfgang Huber and Andy Liaw. - Arguments `unit' and `hmin' of plclust() are now implemented. - prcomp() now accepts complex matrices, and there is biplot() method for its output (in the real case). - dendrograms are slightly better documented, methods working with "label", not "text" attribute. New rev() method for dendr...

...age is based on S4 methods and classes. o Changes in package 'mva': - factanal() now returns the test statistic and P-value formerly computed in the print method. - heatmap() has many more arguments, partly thanks to Wolfgang Huber and Andy Liaw. - Arguments `unit' and `hmin' of plclust() are now implemented. - prcomp() now accepts complex matrices, and there is biplot() method for its output (in the real case). - dendrograms are slightly better documented, methods working with "label", not "text" attribute. New rev() method for dendr...