| 1 | 1 args = commandArgs(); | 
|  | 2 input_file=args[4]; | 
|  | 3 #input_file="control_a.0.1.flt.ratio.tmpca"; | 
|  | 4 #print (input_file); | 
|  | 5 | 
|  | 6 | 
|  | 7 library(MASS); | 
|  | 8 | 
|  | 9 p=array(0,dim=1000); | 
|  | 10 | 
|  | 11 for (i in 0:999) | 
|  | 12 { | 
|  | 13 	        p[i]=0.001 | 
|  | 14 } | 
|  | 15 | 
|  | 16 if ( file.info(input_file)["size"]>0 ) | 
|  | 17 { | 
|  | 18 | 
|  | 19 data=read.table(input_file); | 
|  | 20 col=1; | 
|  | 21 x=data[,col]; | 
|  | 22 x1=x; | 
|  | 23 if (length(x)>10) | 
|  | 24 { | 
|  | 25 	x1[x==0] <- .Machine$double.eps; | 
|  | 26 	x1[x==1] <- (1-.Machine$double.eps); | 
|  | 27 	xbar=mean(x1) | 
|  | 28 	xvar=var(x1) | 
|  | 29 	a <- (xbar*(1-xbar)/xvar - 1)*xbar | 
|  | 30 	b <- (1-xbar)*a/xbar | 
|  | 31 	(f=fitdistr(x1,"beta",list(shape1=a,shape2=b))) | 
|  | 32 	for (i in 0:999) | 
|  | 33 	{ | 
|  | 34 		p[i]=dbeta(i/1000,f[["estimate"]][["shape1"]],f[["estimate"]][["shape2"]]) | 
|  | 35 	} | 
|  | 36 } | 
|  | 37 | 
|  | 38 } | 
|  | 39 write(p,file=paste(input_file,"fit",sep="."),ncolumns=1); |