search for: cumlat

...eet Bin1_Acres=Bin1_main[[1]]*43560 #Separates TAZ data from main data Bin1_TAZ=Bin1_main[[2]] #Separates TAZ data from main data and converts acres to square feet Bin1_TAZvacant=Bin1_main[[3]]*43560 #Sums each parcel acreage data of the bin Bin1Acres_sum=sum(Bin1_Acres) #Creates data frame of cumlative percentages of each parcel of bin Bin1_cumper=cumsum(Bin1_Acres/Bin1Acres_sum) #Calculates the probability of choosing particular parcel from bin Bin1_parprob=abs(1-Bin1_cumper) #Combines parcel acreage data and cumlative percentage data Bin1Main.data = cbind(Bin1_Acres,Bin1_parprob,Bin1_TAZ,B...

...i_Acres=Bin$i_main[[1]]*43560 #Separates TAZ data from main data Bin$i_TAZ=Bin$i_main[[2]] #Separates TAZ data from main data and converts acres to square feet Bin$i_TAZvacant=Bin$i_main[[3]]*43560 #Sums each parcel acreage data of the bin Bin$iAcres_sum=sum(Bin$i_Acres) #Creates data frame of cumlative percentages of each parcel of bin Bin$i_cumper=cumsum(Bin$i_Acres/Bin$iAcres_sum) #Calculates the probability of choosing particular parcel from bin Bin$i_parprob=abs(1-Bin$i_cumper) #Combines parcel acreage data and cumlative percentage data Bin$iMain.data = cbind(Bin%i_Acres,Bin$i_parprob,Bi...

Dear R-Experts, I was wondering how to fit a cumulative gaussian to a set of empirical data using R. On the R website as well as in the mail archives, I found a lot of help on how to fit a normal density function to empirical data, but unfortunately no advice on how to obtain reasonable estimates of m and sd for a gaussian ogive function. Specifically, I have data from a psychometric function