fullMLE | R Documentation |
Compute the MLEs of a two-sample Poisson rate problem with misclassified data given fallible and infallible datasets.
fullMLE(data, N1, N2, N01, N02)
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 |
These are the closed-form expressions for the MLEs.
a named vector containing the mles of each of the parameters (phi, la12, la21, la22, th1, and th2)
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, 95:122–132.
# 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) ## End(Not run)
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