search for: qres

...ction_begin, + rquotad_quota_transaction_commit, + rquotad_quota_transaction_rollback, + + rquotad_quota_try_alloc, + rquotad_quota_alloc, + rquotad_quota_free, + + rquotad_quota_last_error, + + ARRAY_INIT + }; + + static int + rquota_get(char *host, getquota_args *qargs, getquota_rslt *qres) + { + struct sockaddr_in rhost; + struct hostent *hent; + struct timeval tout; + enum clnt_stat cstat; + CLIENT *clnt = NULL; + int sock = RPC_ANYSOCK; + + hent = gethostbyname(host); + if (!hent) + return -1; + if (hent->h_length > (int)sizeof(rhost.sin_addr)) + return -1; +...

...lt;-match(tymo,monthnames) moeff<-.5*sin(2*pi*moeff/365 + 127) #new version; to have strictly stationary levels of air-pollution #within strata pm10<-2 + .5*moeff[tymofa] + 0.1*ar1 #intercept and proportionality to pm10 coefficients of log-rate al<- -2.5 be<- 1.4 qres<-numeric(samp) glmres<-qres gamres<-qres for(q in 1:samp) { rate<-exp(al + be*pm10) mi<-rpois(length(rate),lambda=rate) date1<-as.Date(startdate) dates<-date1 + (ti-1) tyda<-weekdays(dates) tymo<-months(dates) tyyear<-as.character(dates) for (i in...

...s(a+moeff) tymofa<-match(tymo,monthnames) moeff<-.5*sin(2*pi*moeff/365 + 127) #new version; to have strictly stationary levels of air-pollution #within strata pm10<-2 + .5*moeff[tymofa] + 0.1*ar1 #intercept and proportionality to pm10 coefficients of log-rate al<- -2.5 be<- 1.4 qres<-numeric(samp) glmres<-qres gamres<-qres for(q in 1:samp) { rate<-exp(al + be*pm10) mi<-rpois(length(rate),lambda=rate) date1<-as.Date(startdate) dates<-date1 + (ti-1) tyda<-weekdays(dates) tymo<-months(dates) tyyear<-as.character(dates) for (i in 1:n) { ? ask<-t...

...permissions ... WARNING * Found the following text files with incorrect permissions: * ./R/cbind.dimnames.r * ./R/clean.na.r * ./R/invgauss.r * ./R/my.table.r * ./R/negbingof.r * ./R/numberof.r * ./R/poisgam.r * ./R/progress.meter.r * ./R/qnorm.appr.r * ./R/qres.r * ./R/rowSums.r * ./R/S.princomp.r * ./R/select.range.r * ./R/shapiro.wilk.test.r * ./R/smoothed.df.r * ./R/tri.r * ./R/tweedie.r * ./R/tweedief.r * ./R/weighted.mean1.r * ./R/zzz.R * ./R/weighted.median.r * ./R/plotCI.Rd * ./man/cbind.dimnames....

...permissions ... WARNING * Found the following text files with incorrect permissions: * ./R/cbind.dimnames.r * ./R/clean.na.r * ./R/invgauss.r * ./R/my.table.r * ./R/negbingof.r * ./R/numberof.r * ./R/poisgam.r * ./R/progress.meter.r * ./R/qnorm.appr.r * ./R/qres.r * ./R/rowSums.r * ./R/S.princomp.r * ./R/select.range.r * ./R/shapiro.wilk.test.r * ./R/smoothed.df.r * ./R/tri.r * ./R/tweedie.r * ./R/tweedief.r * ./R/weighted.mean1.r * ./R/zzz.R * ./R/weighted.median.r * ./R/plotCI.Rd * ./man/cbind.dimnames....

Dear Sirs What is the best aproximation to the standardized normal distribution: necessidade = c("sem necessidade","com necessidade") tipo =c("CE-1", "CE-2", "CE-3") dados=c(20,34,44,69,9,3) Tabela =cbind(expand.grid(list(Necessidade=necessidade, Tipo=tipo)), count=dados) Tabela.array=tapply(Tabela$count, Tabela[,1:2], sum) ni =

Dear all, I am running a logistic regression and this is the output: glm(formula = educationUniv ~ brncntr, family = binomial) Deviance Residuals: Min 1Q Median 3Q Max # ???? ????? ?? ???????? -0.8825 -0.7684 -0.7684 1.5044 1.6516 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -1.06869 0.01155 -92.487 <2e-16 *** brncntrNo