flexorhtest.pvalue | R Documentation |
These functions evaluate the p-values from an individual or multiple flexible order restricted hypothesis testing.
flexisoreg.pvalue(y, x, lambda=0, alpha.location=1, alpha.adjacency=0.5, B=100) flexisoreg.poolpvalues(m, x, lambda=0, alpha.location=1, alpha.adjacency=0.5, B=100) flexmonoreg.pvalue(y, x, lambda=0, alpha.location=1, alpha.adjacency=0.5, B=100) flexmonoreg.poolpvalues(m, x, lambda=0, alpha.location=1, alpha.adjacency=0.5, B=100)
m |
a matrix of observed data, where samples are in columns and variables are in rows |
y |
a vector of observed data |
x |
a vector of ordinal group labels correponding to |
lambda |
a lower location bound for partitioned groups other than the first one |
alpha.location |
α level for the upper-tailed one-sample t-test with lower bound |
alpha.adjacency |
α level for the upper-tailed two-sample t-test to evaluate the magnitude of nondecreasing order |
B |
the number of permutations for p-value assessment |
flexisoreg.pvalue
and flexmonoreg.pvalue
provide the permutation p-value for an individual flexible order restricted hypothesis testing.
flexisoreg.poolpvalues
and flexmonoreg.poolpvalues
provide the pooled permutation p-values for multiple flexible order restricted hypothesis testing.
flexisoreg.pvalue
and flexmonoreg.pvalue
return a permutation p-value.
flexisoreg.poolpvalues
and flexmonoreg.poolpvalues
return a vector of pooled permutation p-values.
These functions are used in conjunction with flexisoreg
, flexisoreg.stat
, flexmonoreg
and flexmonoreg.stat
.
Yinglei Lai ylai@gwu.edu
Yinglei Lai (2007) A flexible order restricted hypothesis testing and its application to gene expression data. Technical Report
#generate ordinal group lables x x <- runif(100)*6 x <- round(x,0)/3 #generate true values z z <- round(x^2,0) #generate 6 vectors in a matrix for observed values, some noises and some not m <- array(double(6*100), dim=c(6,100)) for(k in 1:3) m[k,] <- rnorm(100) for(k in 4:6) m[k,] <- z + rnorm(100) #print default results par(mfrow=c(2,3)) for(k in 1:6){ print(paste("The ", k, "-th vector", sep="")) y <- m[k,] plot(x,y,main=k) print(flexisoreg.stat(y,x)) print(flexisoreg.pvalue(y,x,B=20)) print(flexisoreg.stat(y,0-x)) print(flexisoreg.pvalue(y,0-x,B=20)) print(flexmonoreg.stat(y,x)) print(flexmonoreg.pvalue(y,x,B=20)) } flexisoreg.poolpvalues(m, x, B=20) flexmonoreg.poolpvalues(m, x, B=20)
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