Comments on ‘Fitting continuous-time and discrete-time models using discrete-time data and their application’

This short paper extends the results of the paper on ‘Fitting continuous-time and discrete-time models using discrete-time data and their application’ (Zhu J., Shieh, L. S. and Yates, R. E.: Appl. Math. Modelling 1985, 9, 93) to systems with multiple poles.     

Simple discrete-time malarial models

We investigate dynamics of mosquito population models under two assumptions, respectively, and then formulate simple discrete-time compartmental susceptible-exposed-infective-recovered models for the malaria transmission based on the mosquito population models. We show that the mosquito population models either have robust dynamics or exhibit period-doubling bifurcation depending on the model assumptions. We derive a formula for the reproductive number of infection for the malaria model, which determines the stability of the infection-free fixed point. We then determine the existence of endemic fixed points for the malaria models. Using numerical simulations, we demonstrate that the dynamical characteristics of the mosquito populations, such as the global stability of the endemic fixed point and the appearance of a period-doubling bifurcation, are reflected in the dynamics of the malaria transmission.     

Risk-sensitive and risk-neutral control for continuous-time hidden Markov models

In this paper the optimal control of a continuous-time hidden Markov model is discussed. The risk-sensitive problem involves a cost function which has an exponential form and a risk parameter, and is solved by defining an appropriate information state and dynamic programming. As the risk parameter tends to zero, the classical risk-neutral optimal control problem is recovered. The limits are proved using viscosity solution methods.The first author wishes to acknowledge the funding of the activities of the Cooperative Research Centre for Robust and Adaptive Systems by the Australian Commonwealth Government under the Cooperative Research Centers Program. The support of NSERC Grant A7964 is acknowledged by the second author, as is the hospitality of the Department of Systems Engineering and the Cooperative Research Centre for Robust and Adaptive Systems, Australian National University, in July 1993.     

Recent models in data envelopment analysis: Theory and applications

A critical review of the recent models of data envelopment analysis (DEA) is attempted here. Three new lines of approach involving dynamic changes in parameters, the error correction models and a stochastic sensitivity analysis are discussed in some detail. On the applications side, two new formulations are presented and discussed, e.g. a model of technical change and a cost frontier for testing economies of scale and adjustment due to risk factors. Thus the critical review of recent DEA models of productivity measurement provides new insight into the frontier of research in this field.     

Value preserving portfolio strategies in continuous-time models

We present a new approach for continuous-time portfolio strategies that relies on the principle of value preservation. This principle was developed by Hellwig (1987) for general economic decision and pricing models. The key idea is that an investor should try to consume only so much of his portfolio return that the future ability of the portfolio should be kept constant over time. This ensures that the portfolio will be a long lasting source of income. We define a continuous-time market setting to apply the idea of Hellwig to securities markets with continuous trading and examine existence (and uniqueness) of value-preserving strategies in some widely used market models. Further, we discuss the existence of such strategies in markets with constraints and incompleteness.Parts of the paper were written during the author's visit at the Isaac Newton Institute for Mathematical Science in Cambridge, UK. The revised version was prepared when the author was on sabbatical at the Dept. of Electrical and Electronic Engineering, Imperial College of Science and Technology, London. The author appreciates both these invitations very much.     

Adaptive control of three continuous-time portfolio and consumption models

An economic application of adaptive control is presented using three continuous time portfolio and consumption models that are natural generalizations of a model of Merton. In these models of the wealth of an individual investor, it is assumed that the various parameters are deterministic functions of time or stochastic processes. An adaptive control problem arises for each of these models when it is assumed that the average return rate of the risky asset, which is either a deterministic function or a stochastic process, is not observed. For these models, a recursive family of estimators of the average return rate of the risky asset is given based on the observations of the wealth. These estimates are used in the control of the wealth equation.This research was partially supported by NSF Grant No. ECS-84-03286-A01 and by University of Kansas General Research Allocation No. 3806-XO-0038.     

Stochastic comparisons and bounds for aging renewal process shock models and their applications

Sharp comparisons between aging renewal process shock models and the corresponding Esary-Marshall-Proschan (EMP) shock model are considered. The usefulness of such comparisons derive from the simplicity of the latter models. Simple conditions under which such aging renewal process shock models are stochastically ordered relative to a corresponding EMP-model are derived. Applications to renewal functions and single server queues are indicated.     

Transformations between discrete-time and continuous-time algebraic Riccati equations

We introduce a transformation between the discrete-time and continuous-time algebraic Riccati equations. We show that under mild conditions the two algebraic Riccati equations can be transformed from one to another, and both algebraic Riccati equations share common Hermitian solutions. The transformation also sets up the relations about the properties, commonly in system and control setting, that are imposed in parallel to the coefficient matrices and Hermitian solutions of two algebraic Riccati equations. The transformation is simple and all the relations can be easily derived. We also introduce a generalized transformation that requires weaker conditions. The proposed transformations may provide a unified tool to develop the theories and numerical methods for the algebraic Riccati equations and the associated system and control problems.     

Modeling loss data using composite models

We develop several new composite models based on the Weibull distribution for heavy tailed insurance loss data. The composite model assumes different weighted distributions for the head and tail of the distribution and several such models have been introduced in the literature for modeling insurance loss data. For each model proposed in this paper, we specify two parameters as a function of the remaining parameters. These models are fitted to two real insurance loss data sets and their goodness-of-fit is tested. We also present an application to risk measurements and compare the suitability of the models to empirical results.     

Ruin-based risk measures in discrete-time risk models

For an insurance company, effective risk management requires an appropriate measurement of the risk associated with an insurance portfolio. The objective of the present paper is to study properties of ruin-based risk measures defined within discrete-time risk models under a different perspective at the frontier of the theory of risk measures and ruin theory. Ruin theory is a convenient framework to assess the riskiness of an insurance business. We present and examine desirable properties of ruin-based risk measures. Applications within the classical discrete-time risk model and extensions allowing temporal dependence are investigated. The impact of the temporal dependence on ruin-based risk measures within those different risk models is also studied. We discuss capital allocation based on Euler’s principle for homogeneous and subadditive ruin-based risk measures.     

On equivalence of pencils from discrete-time and continuous-time control

We study two matrix pencils that arise, respectively, in discrete-time and continuous-time optimal and robust control. We introduce a one-to-one transformation between these two pencils. We show that for the pencils under the transformation, their regularity is preserved and their eigenvalues and deflating subspaces are equivalently related. The eigen-structures of the pencils under consideration have strong connections with the associated control problems. Our result may be applied to connect the discrete-time and continuous-time control problems and eventually lead to a unified treatment of these two types of control problems.     

Fitting mixed-effects models when data are left truncated

Damage sizes, i.e. all damages occurring to a policy and not only those that are reported to an insurance company, are modelled as a linear mixed model. Only those damages that are larger than their deductibles are reported to the company, and this fact should be taken into account when analyzing such data. In statistical terms, the problem is to make inference in a linear mixed model with left truncated data. Estimation methods based on a Monte Carlo simulation of the likelihood are proposed, and extensive simulations to evaluate the quality of the methods are reported. The proposed methods are then used to analyze claimsizes for some marine insurance data, where shipowners represent random effects and technical data about the ships represent fixed effects.     

Compatibility of multi-wave panel data and the continuous-time homogeneous Markov chain. An analysis of a continuous-time process by means of discrete-time longitudinal observations

Multi-wave panel data are observations at two or more points in time on a continuously changing attribute of interest (e.g. behaviour). In this paper, the adequacy of the continuous-time homogeneous Markov chain (CTHMC) model is assessed for describing the process of change underlying such data. In the case of equidistant observational times, it may happen that the maximum-likelihood estimate of the transition probability matrix between successive observational times from these data cannot arise from a CTHMC. It is investigated whether this event can be ascribed to chance through the introduction of an hypothesis test. © 1998 John Wiley & Sons, Ltd.     

Diagnostics in Birnbaum–Saunders accelerated life models with an application to fatigue data

In industrial statistics, there is great interest in predicting with precision lifetimes of specimens that operate under stress. For example, a bad estimation of the lower percentiles of a life distribution can produce significant monetary losses to organizations due to an excessive amount of warranty claims. The Birnbaum–Saunders distribution is useful for modeling lifetime data. This is because such a distribution allows us to relate the total time until the failure occurs to some type of cumulative damage produced by stress. In this paper, we propose a methodology for detecting influence of atypical data in accelerated life models on the basis of the Birnbaum–Saunders distribution. The methodology developed in this study should be considered in the design of structures and in the prediction of warranty claims. We conclude this work with an application of the proposed methodology on the basis of real fatigue life data, which illustrates its importance in a warranty claim problem. Copyright © 2012 John Wiley & Sons, Ltd.     

An Approximation Method for Improving Dynamic Network Model Fitting

There has been a great deal of interest recently in the modeling and simulation of dynamic networks, that is, networks that change over time. One promising model is the separable temporal exponential-family random graph model (ERGM) of Krivitsky and Handcock, which treats the formation and dissolution of ties in parallel at each time step as independent ERGMs. However, the computational cost of fitting these models can be substantial, particularly for large, sparse networks. Fitting cross-sectional models for observations of a network at a single point in time, while still a nonnegligible computational burden, is much easier. This article examines model fitting when the available data consist of independent measures of cross-sectional network structure and the duration of relationships under the assumption of stationarity. We introduce a simple approximation to the dynamic parameters for sparse networks with relationships of moderate or long duration and show that the approximation method works best in precisely those cases where parameter estimation is most likely to fail—networks with very little change at each time step. We consider a variety of cases: Bernoulli formation and dissolution of ties, independent-tie formation and Bernoulli dissolution, independent-tie formation and dissolution, and dependent-tie formation models.     

Baseline models of spatial population dynamics

To understand human population dynamics fully, before considering complex human agency it may be useful to construct baseline models to see where such agency may and may not be necessary. In fact, the dynamics of human populations may be amenable to mathematical modeling with relatively parsimonious mechanisms. We review some of the more prominent of such models, namely, the spatial Galton-Watson (GW) model, modifications of the GW model that add migration and immigration, and the Bolker-Pacala model, in which mortality (or birth rate) is affected by competition. We show that change in the distribution of population density over the last century for 12 American rural states may be captured by the simplest of the models, the spatial GW model.     

Interactive hidden Markov models and their applications

^** Email: wching{at}hkusua.hku.hk In this paper, we propose an Interactive hidden Markov model(IHMM). In a traditional HMM, the observable states are affecteddirectly by the hidden states, but not vice versa. In the proposedIHMM, the transitions of hidden states depend on the observablestates. We also develop an efficient estimation method for themodel parameters. Numerical examples on the sales demand dataand economic data are given to demonstrate the applicabilityof the model.     

Fitting of curves and surfaces based on interaction of physical relations and experimental data

Two different approaches to the solutions of boundary value problems in mathematical physics are discussed. First, a theoretical model based on an ideal model. The second approach is based on experimental data and a suitable approximation scheme.     

Nonlinear instability in advection-diffusion numerical models

The phenomenon of nonlinear instability, which affects all propagation equations, is simply presented and explained; its origin lies in the numerical dispersion of fundamental solutions by the discrete schemes. Methods to avoid it or to minimize its effects on solutions are proposed and discussed.