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Statistical inference of subcritical strongly stationary Galton–Watson processes with regularly varying immigration

We describe the asymptotic behavior of the conditional least squares estimator of the offspring mean for subcritical strongly stationary Galton– Watson processes with regularly varying immigration with tail index α∈(1, 2). The limit law is the ratio of two dependent stable random variables with indices α∕2 and 2α∕3, respectively, and it has a continuously differentiable density function. We use point process technique in the proofs.

Galton–Watson process with immigration ; Conditional least squares estimator ; Regularly varying distribution ; Strong stationarity ; Point process

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