search for: acreag

...d=FALSE); #Separates Acres data from main data and converts acres to square feet 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 cuml...

...E); #Separates Acres data from main data and converts acres to square feet Bin$i_Acres=Bin$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 a...

...d.out<-sequential.unpaired(number.strata=2, verification.plots=verification.plots, project.n=15, project.mean=100, project.sd=10, allowed.deviation=.05, project.acres=99, min.plots="default") str(unpaired.out) #unpaired.out[[7]][1] ## simulation.unpaired <- function(reps, project.acreage.range = c(99, 110,510,5100,11000), project.mean, project.n.min, project.n.max, project.sd.min, project.sd.max, verification.mean.min, verification.mean.max, number.verification.plots.min, number.verification.plots.max, allowed.deviation=.1, alpha=.05, length.out = 5, min.plots="default")...

...strcpy( s_ptr->stand_name, CHAR(STRING_ELT(get_list_element(sample,"stand.name"), 0)) ); strcpy( s_ptr->legal, CHAR(STRING_ELT(get_list_element(sample,"legal"), 0)) ); s_ptr->elevation = asInteger( get_list_element( sample, "elevation" ) ); s_ptr->acreage = asReal( get_list_element( sample, "acreage" ) ); s_ptr->age = asInteger( get_list_element( sample, "age" ) ); s_ptr->sampled_month = asInteger( get_list_element( sample, "sampled.month" ) ); s_ptr->sampled_day = asInteger( get_list_element( sample,...

Dear All, I have a question about package "ismev", its function "gpd.fit", and interpretation of the results. I used the package ismev to do an extreme value analysis on a fire dataset. Two variables are used in the analysis. The focal variable is acreage burned per fire, ranging from 1 to 5000 acres per fire. In total, there are 69,980 observations. The date covers 1991 to 2008. I created a time variable indexed by day, ranging from 1 (i.e., July/1/1991) to 6,708 (Nov/10/2008). In total, there 6,708 days. I used function "gpd.fit" to est...

...ere part of a pilot to determine if individually fracturing each of the zones would result in better recovery. Prior efforts had evolved from single-stage, limited entry treatments to multiple-stage treatments with composite frac plugs and frac baffles. microelectrophoretically Core tests on offset acreage had revealed that 3 of 10 coal seams had not been stimulated by these treatments and, on average, ten feet of coal was not being effectively stimulated. If the CT fracturing approach is successful in improving this situation, CONSOL calculated that an additional net present value of 1 million coul...