Statistical inference for branching processes with an increasing random number of ancestors
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Publication:1330201
DOI10.1016/0378-3758(94)90212-7zbMath0808.62074OpenAlexW2092834117MaRDI QIDQ1330201
Nikolay M. Yanev, Jean-Pierre Dion
Publication date: 12 July 1994
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/0378-3758(94)90212-7
consistencyasymptotic normalitybranching processmaximum likelihoodleast squares estimationcensored estimatorsrandom number of ancestors
Markov processes: estimation; hidden Markov models (62M05) Branching processes (Galton-Watson, birth-and-death, etc.) (60J80)
Related Items (7)
Parameter estimation for discretely observed linear birth‐and‐death processes ⋮ Quasi- and pseudo-maximum likelihood estimators for discretely observed continuous-time Markov branching processes ⋮ Limit laws of estimators for critical multi-type Galton-Watson processes ⋮ Estimation of the offspring mean in a supercritical branching process with non-stationary immigration ⋮ Limiting Distributions for Multitype Branching Processes ⋮ Relative frequencies in multitype branching processes ⋮ Stock prices as branching processes in random environments: estimation
Cites Work
- Arbres et processus de Bellman-Harris. (Trees and Bellman-Harris processes)
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- THE BEHAVIOUR OF AN ESTIMATOR FOR A SIMPLE BIRTH AND DEATH PROCESS
- Exact distributions of kin numbers in a Galton-Watson process
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- On estimating the variance of the offspring distribution in a simple branching process
- On the Statistics of Branching Processes
- On the Limit Distributions of Some Functionals in Multi-Type Branching Processes
- Asymptotic Behavior of the Extinction Probabilitiesfor Stopped Branching Processes
- Nonparametric estimation of the age of a Galton-Watson branching process
- On the central limit theorem for the sum of a random number of independent random variables
- Least squares estimates in stochastic regression models with applications to identification and control of dynamic systems
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