LCMBounds | R Documentation |
Finds an exact confindence interval for a linear combination of multinomial probabilities
LCMBounds(
Lhat,
weights,
samplesizes,
alpha.upper = 0.025,
alpha.lower = alpha.upper,
rand.samps = 20,
opt.samps = 20,
mass = 1,
power.of.2 = TRUE
)
Lhat |
Observed value of a linear combination of multinomial probabilities that needs a confidence interval (a scalar). |
weights |
A list of numeric vectors that correspond to the multinomial probabilities. |
samplesizes |
A numeric vector of length K, each entry in the vector cooresponds to the sample sizes for the K multinomial experiements. |
alpha.upper |
The amount of probability outside the upper limit of the confidence interval (this produces a (1-alpha.upper-alpha.lower)% CI). |
alpha.lower |
The amount of probability outside the lower limit of the confidence interval. |
rand.samps |
A scalar which directs the alogrithm on how many random samples to try before beginning the optimizing stage. |
opt.samps |
A scalar which directs the alogrithm on how many optimizing steps to make. |
mass |
A scalar tuning parameter. It is not recommended to change it from the default. |
power.of.2 |
A logical tuning parameter. It is not recommended to change it from the default. |
Lhat <- 7.8
weightsA <- list(c(0,1,1),c(2,0,3),c(5,3,0))
samplesizes <- c(20,20,20)
LCMBounds(Lhat,weightsA,samplesizes)
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