search for: closen

...) lon2<-rep(seq(99.5,105.5,by=2),each=4) redcells<-data.frame(lat=lat2,lon=lon2,value=NA) display the red cells rect(lon2-1,lat2-1,lon2+1,lat2+1,border="red",lwd=2) nblackcells<-dim(blackcells)[1] nredcells<-dim(redcells)[1] for(redcell in 1:nredcells) { close4<-rep(NA,4) closen<-1 for(blackcell in 1:nblackcells) { if(abs(blackcells[blackcell,"lat"]-redcells[redcell,"lat"]) < 1 && abs(blackcells[blackcell,"lon"]-redcells[redcell,"lon"]) < 1) { close4[closen]<-blackcells[blackcell,"pop"] close...

..."red" lat/lon values. Here's a basic example: lat<-rep(28:38,11) lon<-rep(98:108,each=11) pop<-sample(80:200,121) blackcells<-list() for(i in 1:121) blackcells[[i]]<-list(lat=lat[i],lon=lon[i],pop=pop[i]) redcell<-list(lat=33.5,lon=100.5,pop=NA) close4<-rep(NA,4) closen<-1 for(i in 1:121) { if(abs(blackcells[[i]]$lat-redcell$lat) < 1 && abs(blackcells[[i]]$lon-redcell$lon) < 1) { close4[closen]<-i closen<-closen+1 } } cat(close4,"\n") redcell$pop<-(blackcells[[close4[1]]]$pop + blackcells[[close4[2]]]$pop + blackcells[[...

Hi R users, I have a question about data processing. I have such a dataset, while each black grid cell has a few attributes and the corresponding attribute values. The latitude and longitude of the center of each grid cell are given also. Then I want to average the attribute values from four adjacent grid cells to get the average value for the center of each red grid cell. Thus, there are the

...=4) > redcells<-data.frame(lat=lat2,lon=lon2,value=NA) > display the red cells > rect(lon2-1,lat2-1,lon2+1,lat2+1,border="red",lwd=2) > nblackcells<-dim(blackcells)[1] > nredcells<-dim(redcells)[1] > for(redcell in 1:nredcells) { > close4<-rep(NA,4) > closen<-1 > for(blackcell in 1:nblackcells) { > if(abs(blackcells[blackcell,"lat"]-redcells[redcell,"lat"]) < 1 && > abs(blackcells[blackcell,"lon"]-redcells[redcell,"lon"]) < 1) { > close4[closen]<-blackcells[blackcell,&quot...

...frame, each row can represent one grid cell, > while the three columns can represent the lati, lon, and pop. Thanks again > for your help. > > for(i in 1:121) { > if(abs(blackcells[[i]]$lat-redcell$lat) < 1 && > abs(blackcells[[i]]$lon-redcell$lon) < 1) { > close4[closen]<-i > closen<-closen+1 > } > } > > On Wed, May 16, 2018 at 2:45 AM, Jim Lemon <drjimlemon at gmail.com> wrote: >> >> Hi lily, >> There are one or two assumptions to be made here. First is that the >> latitude and longitude values of the "black...

...and predicted value so neatly.The simple problem i am finding is that i am having say 200 data values in time series and say i take 150 values for model parameter estimation.Now what i get in matlab is the mean and variance forecast of 51,52nd etc intervals.Now i need to plot the graph showing the closenes of the predicted and actual return values and not the variance .How can i do so???Plzz help in this regard.Will be of great help -- View this message in context: http://www.nabble.com/regarding-Garch-prediction-mechanism-tp16538527p16538527.html Sent from the R help mailing list archive at Nabbl...

Hello R Help Team, I have created graph from weighted adjecency matrix .Is there a way I can find highly connected nodes in Igraph like the Package RBGL does. nathan -- View this message in context: http://www.nabble.com/Highly-Connected-Nodes-in-Igraph-tp22377522p22377522.html Sent from the R help mailing list archive at Nabble.com.