Chao1Model <- function(s,r,observedCount,n,frequency,singletons,maximumObservation) {
f1 <- singletons
##estimated total species
sHatTotal <- 0.0
##Standard Error
se <- 0.0
seFlag <- 0
##if there are doubletons
if (frequency[1] == 2 || frequency[2] == 2) {
sHatTotal <- s[maximumObservation] + (pow(f1, 2) / (2.0 * observedCount[2]))
temp <- f1 / observedCount[2]
se <- observedCount[2] * ((0.5 * (temp * temp)) +
(pow(temp, 3)) + (0.25 * (pow(temp, 4))))
if (se >= 0.0)
{
se <- sqrt(se)
seFlag <- 1
}
} else {
sHatTotal <- s[maximumObservation] + (f1 * (f1 - 1.0) / 2.0)
se = (0.5 * f1 * (f1 - 1.0)) + (0.25 * f1 * 2.0 *
(f1 - 1.0) * 2.0 * (f1 - 1.0)) - (0.25 * f1 * f1 * f1 * f1 /
sHatTotal)
if (se >= 0.0) {
se <- sqrt(se)
seFlag <- 1
}
}
sHatSubset <- sHatTotal - (s[maximumObservation] - s[r])
if (seFlag == 1) {
##Confidence Bounds
boundsCheck <- GetConfidenceBounds(r, se, sHatSubset, s, maximumObservation)
}
output <- data.frame("Model" = "Chao1",
"Cutoff" = r,
"Estimate" = CheckOutput(sHatTotal),
"SE" = CheckOutput(se),
"LCB"= CheckOutput(boundsCheck$lcb),
"UCB" = CheckOutput(boundsCheck$ucb),
"chiSq" = NA,
"AIC" = NA,
"AICc" = NA,
"GOF0" = NA,
"GOF5" = NA,
"T1"= NA,
"T2"= NA,
"T3"= NA,
"T4"=NA,
"T5"=NA,
"T6"=NA,
"T7"=NA)
}
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