| 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 "variables" consisting of linear
equations in the unknowns.
Var = EqA.x+EqB
varsample (X, EqA, EqB=NULL)
X |
matrix whose rows contain the sampled values of the unknowns
|
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 <karline.soetaert@nioz.nl>
Minkdiet, for a description of the Mink diet example.
varranges, to estimate ranges of inverse variables.
xsample, to randomly sample the lsei problem.
# 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(ncol = 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")