Rd file 'FindOptPower.Rd':
  \usage lines wider than 90 characters:
     FindOptPower(cost, sample.size, MAF, OR, error, costPerExp = 18915, costPerPool = 970, costPerX = 300, lower.P = 20, upper.P = 400, low ... [TRUNCATED]
  \examples lines wider than 100 characters:
     example.1 <- FindOptPower(cost=452915, sample.size=5000, MAF=0.03, OR=2, error=0.01, upper.P=200, Number.Grids=20)

Rd file 'PlotOptPower.Rd':
  \usage lines wider than 90 characters:
     PlotOptPower(opt.design.results, save.contour = FALSE, contour.filename = NA, plot.3d = TRUE)
  \examples lines wider than 100 characters:
     example.1 <- FindOptPower(cost=452915, sample.size=5000, MAF=0.03, OR=2, error=0.01, upper.P=200, Number.Grids=20)
     sample.good <- subset(newdata, subset=(newdata$is.valid.design & newdata$upper.sample.good), select=c(P,N.p))
     # # filled.contour(x=log(newdata.N.p), y=log(newdata.P), pred.power, plot.title = title(main = "Grid Search of Optimal Power", xlab = e ... [TRUNCATED]
     filled.contour(x=log(newdata.N.p), y=log(newdata.P), pred.power, plot.title = title(main = "Grid Search of Optimal Power", xlab = expre ... [TRUNCATED]
     description <- bquote(paste("Scenario: VAF=", .(as.numeric(scenario.set["MAF"])), " OR=", .(round(as.numeric(scenario.set["OR"]), digit ... [TRUNCATED]
     plot3d(log(newdata.N.p), log(newdata.P), ln.Xmean, type = "n", xlab="ln(Np)", ylab="ln(P)", zlab="ln(lambda)")
                     if(i==1) x.final <- rbind(x.origin, x.temp)     else x.final <- rbind(x.final, x.temp)
     lines3d(RefineVector(log(sample.N.p),10), RefineVector(log(sample.P),10), RefineVector(log(sample.points.z),10)+0.2, color=2, alpha=0.6 ... [TRUNCATED]

Rd file 'ShowOptDesign.Rd':
  \examples lines wider than 100 characters:
     example.1 <- FindOptPower(cost=700000, sample.size=5000, MAF=0.03, OR=2, error=0.01, upper.P=200, Number.Grids=50)
     designs.good <- subset(opt.design.results[[5]], subset=(is.valid.design & upper.sample.good & Xmean.good))

Rd file 'hiPOD-package.Rd':
  \examples lines wider than 100 characters:
     example.1 <- FindOptPower(cost=452915, sample.size=5000, MAF=0.03, OR=2, error=0.01, upper.P=200, Number.Grids=20)
     PlotOptPower(example.1, save.contour=TRUE, contour.filename=paste(proj.Dir, "/example1_contour.bmp",sep=""))
     ######## Example 2: A realist example comparing with individual sequencing with 200 individuals 4X each
     PlotOptPower(example.2, save.contour=TRUE, contour.filename=paste(proj.Dir, "/example2_contour.bmp",sep=""))
             # example.3 <- FindOptPower(cost=cost.3, sample.size=5000, MAF=0.03, OR=2, error=0.01, costPerExp=CostPerExp.3, costPerPool=Cos ... [TRUNCATED]
             # PlotOptPower(example.3, save.contour=TRUE, contour.filename=paste(proj.Dir, "/example3_contour_CostPerX=", CostPerX.3,".bmp", ... [TRUNCATED]

Rd file 'predictPoolNCP.Rd':
  \examples lines wider than 100 characters:
     covariates <- c(1, MAF, log(OR), error, P, Xmean, N.p, (P^(1/3)), (Xmean^(1/3)), (N.p^(1/3)), (log(OR)^2), MAF*log(OR), Xmean*N.p, MAF* ... [TRUNCATED]

These lines will be truncated in the PDF manual.