scholarly journals Asymptotics of Symmetric Compound Poisson Population Models

2014 ◽  
Vol 24 (1) ◽  
pp. 216-253 ◽  
Author(s):  
THIERRY HUILLET ◽  
MARTIN MÖHLE
Keyword(s):  
Transition Probabilities ◽  
Domain Of Attraction ◽  
Local Limit ◽  
Population Models ◽  
Process Models ◽  
Saddle Point Method ◽  
Regularity Conditions ◽  
Compound Poisson ◽  
Poisson Models ◽  
Simply Generated Trees

Compound Poisson population models are particular conditional branching process models. A formula for the transition probabilities of the backward process for general compound Poisson models is verified. Symmetric compound Poisson models are defined in terms of a parameter θ ∈ (0, ∞) and a power series φ with positive radius r of convergence. It is shown that the asymptotic behaviour of symmetric compound Poisson models is mainly determined by the characteristic value θrφ′(r−). If θrφ′(r−)≥1, then the model is in the domain of attraction of the Kingman coalescent. If θrφ′(r−) < 1, then under mild regularity conditions a condensation phenomenon occurs which forces the model to be in the domain of attraction of a discrete-time Dirac coalescent. The proofs are partly based on the analytic saddle point method. They draw heavily from local limit theorems and from results of S. Janson on simply generated trees, conditioned Galton-Watson trees, random allocations and condensation. Several examples of compound Poisson models are provided and analysed.

Random walks and periodic continued fractions

1985 ◽  
Vol 17 (1) ◽  
pp. 67-84 ◽  
Author(s):  
Wolfgang Woess
Keyword(s):  
Random Walks ◽  
Harmonic Functions ◽  
Limit Theorems ◽  
Continued Fraction ◽  
Transition Probabilities ◽  
Local Limit ◽  
Periodic Sequence ◽  
Nearest Neighbour ◽  
Continued Fraction Expansions ◽  
Local Limit Theorems

Nearest-neighbour random walks on the non-negative integers with transition probabilities p0,1 = 1, pk,k–1 = gk, pk,k+1 = 1– gk (0 < gk < 1, k = 1, 2, …) are studied by use of generating functions and continued fraction expansions. In particular, when (gk) is a periodic sequence, local limit theorems are proved and the harmonic functions are determined. These results are applied to simple random walks on certain trees.

MULTIVARIATE AUTOREGRESSION OF ORDER ONE WITH INFINITE VARIANCE INNOVATIONS

2008 ◽  
Vol 24 (3) ◽  
pp. 677-695 ◽  
Author(s):  
M. Zarepour ◽  
S.M. Roknossadati
Keyword(s):  
Autoregressive Model ◽  
Domain Of Attraction ◽  
Ordinary Least Squares ◽  
Infinite Variance ◽  
Regularity Conditions ◽  
Vector Autoregressive Model ◽  
Stable Law ◽  
Limiting Behavior ◽  
Vector Autoregressive ◽  
Multivariate Autoregression

We consider the limiting behavior of a vector autoregressive model of order one (VAR(1)) with independent and identically distributed (i.i.d.) innovations vector with dependent components in the domain of attraction of a multivariate stable law with possibly different indices of stability. It is shown that in some cases the ordinary least squares (OLS) estimates are inconsistent. This inconsistency basically originates from the fact that each coordinate of the partial sum processes of dependent i.i.d. vectors of innovations in the domain of attraction of stable laws needs a different normalizer to converge to a limiting process. It is also revealed that certain M-estimates, with some regularity conditions, as an appropriate alternative, not only resolve inconsistency of the OLS estimates but also give higher consistency rates in all cases.

scholarly journals RUIN PROBABILITY UNDER COMPOUND POISSON MODELS WITH RANDOM DISCOUNT FACTOR

2004 ◽  
Vol 18 (1) ◽  
pp. 55-70 ◽  
Author(s):  
Kai W. Ng ◽  
Hailiang Yang ◽  
Lihong Zhang
Keyword(s):  
Ruin Probability ◽  
Risk Model ◽  
Poisson Model ◽  
Convergence Result ◽  
Discount Factor ◽  
Insurance Risk ◽  
Compound Poisson ◽  
Analysis Techniques ◽  
Surplus Process ◽  
Poisson Models

In this article, we consider a compound Poisson insurance risk model with a random discount factor. This model is also known as the compound filtered Poisson model. By using some stochastic analysis techniques, a convergence result for the discounted surplus process, an expression for the ruin probability, and the upper bounds for the ruin probability are obtained.

Modeling the effect of erosion on crop production

1987 ◽  
Vol 24 (4) ◽  
pp. 787-797 ◽  
Author(s):  
P. Todorovic ◽  
J. Gani
Keyword(s):  
Crop Yield ◽  
Crop Production ◽  
Transition Probabilities ◽  
Past History ◽  
Random Variable ◽  
Linear Integral Equation ◽  
Regularity Conditions ◽  
Almost Everywhere ◽  
Stationary Transition ◽  
Linear Integral

This paper is concerned with a model for the effect of erosion on crop production. Crop yield in the year n is given by X(n) = YnLn, where is a sequence of strictly positive i.i.d. random variables such that E{Y1} <∞, and is a Markov chain with stationary transition probabilities, independent of . When suitably normalized, leads to a martingale which converges to 0 almost everywhere (a.e.) as n → ∞. In addition, for large n, the distribution of Ln is approximately lognormal. The conditional expectations and probabilities of , given the past history of the process, are determined. Finally, the asymptotic behaviour of the total crop yield is discussed. It is established that under certain regularity conditions Sn converges a.e. to a finite-valued random variable S whose Laplace transform can be obtained as the solution of a Volterra-type linear integral equation.

COMPOUND POISSON CLAIMS RESERVING MODELS: EXTENSIONS AND INFERENCE

2018 ◽  
Vol 48 (3) ◽  
pp. 1137-1156 ◽  
Author(s):  
Shengwang Meng ◽  
Guangyuan Gao
Keyword(s):  
Linear Models ◽  
Mean Squared Error ◽  
Predictive Distribution ◽  
Compound Poisson ◽  
Poisson Models ◽  
Squared Error ◽  
Run Off ◽  
Mean And Variance ◽  
The Individual ◽  
Over Dispersion

AbstractWe consider compound Poisson claims reserving models applied to the paid claims and to the number of payments run-off triangles. We extend the standard Poisson-gamma assumption to account for over-dispersion in the payment counts and to account for various mean and variance structures in the individual payments. Two generalized linear models are applied consecutively to predict the unpaid claims. A bootstrap is used to estimate the mean squared error of prediction and to simulate the predictive distribution of the unpaid claims. We show that the extended compound Poisson models make reasonable predictions of the unpaid claims.

Approximating kth-order two-state Markov chains

1992 ◽  
Vol 29 (4) ◽  
pp. 861-868 ◽  
Author(s):  
Y. H. Wang
Keyword(s):  
Markov Chains ◽  
Total Variation ◽  
Upper Bound ◽  
Transition Probabilities ◽  
Random Variable ◽  
Poisson Random Variable ◽  
Compound Poisson ◽  
Stationary Transition

In this paper, we consider kth-order two-state Markov chains {Xi} with stationary transition probabilities. For k = 1, we construct in detail an upper bound for the total variation d(Sn, Y) = Σx |𝐏(Sn = x) − 𝐏(Y = x)|, where Sn = X1 + · ··+ Xn and Y is a compound Poisson random variable. We also show that, under certain conditions, d(Sn, Y) converges to 0 as n tends to ∞. For k = 2, the corresponding results are given without derivation. For general k ≧ 3, a conjecture is proposed.

Random walks and periodic continued fractions

1985 ◽  
Vol 17 (01) ◽  
pp. 67-84 ◽  
Author(s):  
Wolfgang Woess
Keyword(s):  
Random Walks ◽  
Harmonic Functions ◽  
Limit Theorems ◽  
Continued Fraction ◽  
Transition Probabilities ◽  
Local Limit ◽  
Periodic Sequence ◽  
Nearest Neighbour ◽  
Continued Fraction Expansions ◽  
Local Limit Theorems

Nearest-neighbour random walks on the non-negative integers with transition probabilitiesp0,1= 1,pk,k–1=gk,pk,k+1= 1–gk(0 &lt;gk&lt; 1,k= 1, 2, …) are studied by use of generating functions and continued fraction expansions. In particular, when (gk) is a periodic sequence, local limit theorems are proved and the harmonic functions are determined. These results are applied to simple random walks on certain trees.

Asymptotic behaviour for random walks in random environments

1999 ◽  
Vol 36 (2) ◽  
pp. 334-349 ◽  
Author(s):  
S. Alili
Keyword(s):  
Random Walk ◽  
Limit Theorems ◽  
Transition Probabilities ◽  
Invariant Probability Measure ◽  
Random Environments ◽  
Regularity Conditions ◽  
Large Numbers ◽  
Random Transition ◽  
Independent Case ◽  
Uniquely Ergodic

In this paper we consider limit theorems for a random walk in a random environment, (Xn). Known results (recurrence-transience criteria, law of large numbers) in the case of independent environments are naturally extended to the case where the environments are only supposed to be stationary and ergodic. Furthermore, if ‘the fluctuations of the random transition probabilities around are small’, we show that there exists an invariant probability measure for ‘the environments seen from the position of (Xn)’. In the case of uniquely ergodic (therefore non-independent) environments, this measure exists as soon as (Xn) is transient so that the ‘slow diffusion phenomenon’ does not appear as it does in the independent case. Thus, under regularity conditions, we prove that, in this case, the random walk satisfies a central limit theorem for any fixed environment.

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