poisDoubleSamp (version 1.1.1)

fullMLE: Compute the full MLEs

Description

Compute the MLEs of a two-sample Poisson rate problem with misclassified data given fallible and infallible datasets.

Usage

fullMLE(data, N1, N2, N01, N02)

Arguments

data

the vector of counts of the fallible data (z11, z12, z21, z22) followed by the infallible data (m011, m012, m021, m022, y01, y02)

N1

the opportunity size of group 1 for the fallible data

N2

the opportunity size of group 2 for the fallible data

N01

the opportunity size of group 1 for the infallible data

N02

the opportunity size of group 2 for the infallible data

Value

a named vector containing the mles of each of the parameters (phi, la12, la21, la22, th1, and th2)

Details

These are the closed-form expressions for the MLEs.

References

Kahle, D., P. Young, B. Greer, and D. Young (2016). "Confidence Intervals for the Ratio of Two Poisson Rates Under One-Way Differential Misclassification Using Double Sampling." Computational Statistics & Data Analysis, 95:122<U+2013>132.

Examples

# NOT RUN {
# small example
z11 <- 34; z12 <- 35; N1 <- 10;
z21 <- 22; z22 <- 31; N2 <- 10;
m011 <- 9; m012 <- 1; y01 <- 3; N01 <- 3;
m021 <- 8; m022 <- 8; y02 <- 2; N02 <- 3;
data <- c(z11, z12, z21, z22, m011, m012, m021, m022, y01, y02)

fullMLE(data, N1, N2, N01, N02)


# }
# NOT RUN {
# big example :
z11 <- 477; z12 <- 1025; N1 <- 16186;
z21 <- 255; z22 <- 1450; N2 <- 18811;
m011 <- 38;  m012 <- 90; y01 <- 15; N01 <- 1500;
m021 <- 41; m022 <- 200; y02 <-  9; N02 <- 2500;
data <- c(z11, z12, z21, z22, m011, m012, m021, m022, y01, y02)

fullMLE(data, N1, N2, N01, N02)


# }
# NOT RUN {
# }