varsample {limSolve} | R Documentation |
Uses random samples of an under- or overdetermined linear problem to estimate the distribution of equations
Based on a random sample of x (e.g. produced with xsample
), produces the corresponding set of
inverse "variables" described by the linear equations
Var = EqA.x+EqB
varsample(X, EqA, EqB=NULL)
X |
matrix whose rows contain the sampled values of the unknowns x in EqA*x-EqB |
EqA |
numeric matrix containing the coefficients that define the variables |
EqB |
numeric vector containing the right-hand side of the variable equation |
a matrix whose rows contain the sampled values of the variables
Karline Soetaert <k.soetaert@nioo.knaw.nl>
# The probability distribution of vertebrate and invertebrate # food in the diet of Mink # food items of Mink are (in that order): # fish mussels crabs shrimp rodents amphipods ducks # V I I I V I V # V= vertebrate, I = invertebrate # In matrix form: VarA <- matrix(nc=7, byrow=TRUE,data=c( 0, 1, 1, 1, 0, 1, 0, # invertebrates 1, 0, 0, 0, 1, 0, 1)) # vertebrates # first sample the Minkdiet problem E <- rbind(Minkdiet$Prey,rep(1,7)) F <- c(Minkdiet$Mink,1) X <- xsample(E=E,F=F,G=diag(7),H=rep(0,7),iter=1000)$X #then determine Diet Composition in terms of vertebrate and invertebrate food DC <- varsample(X=X,EqA=VarA) hist(DC[,1],freq=FALSE,xlab="fraction", main="invertebrate food in Mink diet",col="lightblue")