Nonparametric estimation and adaptive control in a class of finite Markov decision chains

We consider a class of Markov decision processes withfinite state and action spaces which, essentially, is determined by the following condition: The state space isirreducible under the action of any stationary policy. However, except by this restriction, the transition law iscompletely unknown to the controller. In this context, we find a set of policies under which thefrequency estimators of the transition law are strongly consistent and then, this result is applied to constructadaptive asymptotically discount-optimal policies.Dedicated to Professor Truman O. Lewis, on the occasion of his sixtieth birthdayThis research was supported in part by the Third World Academy of Sciences (TWAS) under Grant TWAS RG MP 898-152, and in part by the Consejo Nacional de Ciencia y Tecnología (CONACYT) under Grant A128CCOEO550 (MT-2).     

Amine‐blocked polyisocyanates. I. Synthesis of novel N‐methylaniline‐blocked polyisocyanates and deblocking studies using hot‐stage fourier transform infrared spectroscopy

A series of substituted N‐methylaniline‐blocked polyisocyanates based on 4,4′‐methylenebis(phenyl isocyanate) and poly(tetrahydrofuran) were prepared and characterized thoroughly with FTIR, ¹H NMR, and ¹³C NMR spectroscopy methods. Compared with unsubstituted N‐methylaniline, a blocking agent with an electron‐releasing substituent at the para position took a shorter time, whereas those with an electron‐releasing substituent at the ortho position or an electron‐withdrawing substituent at the ortho and para positions took longer times for the blocking reaction. The thermal dissociation reactions of blocked polyisocyanates were carried out with an FTIR spectrophotometer attached to hot‐stage accessories under dynamic and isothermal conditions. The dynamic method was used to determine the deblocking temperature, and the isothermal method was used to calculate the deblocking kinetics and activation parameters. The cure times of blocked polyisocyanates with hydroxyl‐terminated polybutadiene were also determined. The deblocking temperatures, the results of cure‐time studies, and the kinetic parameters revealed that the thermal dissociation of the N‐methylaniline‐blocked polyisocyanates was retarded by electron‐donating substituents and facilitated by electron‐withdrawing substituents. The action of N‐methylanilines as blocking agents for isocyanate was explained by the formation of a four‐center, intramolecularly hydrogen‐bonded ring structure during the thermal dissociation of the blocked polyisocyanates. The formation of such a hydrogen‐bonded ring structure was confirmed and supported by variable‐temperature ¹H NMR studies and entropy parameters, respectively. © 2006 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 45: 1557–1570, 2007     

Pattern Search Method for Discrete <Emphasis Type="Italic">L</Emphasis><Subscript>1</Subscript>–Approximation

We propose a pattern search method to solve a classical nonsmooth optimization problem. In a deep analogy with pattern search methods for linear constrained optimization, the set of search directions at each iteration is defined in such a way that it conforms to the local geometry of the set of points of nondifferentiability near the current iterate. This is crucial to ensure convergence. The approach presented here can be extended to wider classes of nonsmooth optimization problems. Numerical experiments seem to be encouraging. This work was supported by M.U.R.S.T., Rome, Italy.     

Randomly censored partially linear single-index models

This paper proposes a method for estimation of a class of partially linear single-index models with randomly censored samples. The method provides a flexible way for modelling the association between a response and a set of predictor variables when the response variable is randomly censored. It presents a technique for “dimension reduction” in semiparametric censored regression models and generalizes the existing accelerated failure-time models for survival analysis. The estimation procedure involves three stages: first, transform the censored data into synthetic data or pseudo-responses unbiasedly; second, obtain quasi-likelihood estimates of the regression coefficients in both linear and single-index components by an iteratively algorithm; finally, estimate the unknown nonparametric regression function using techniques for univariate censored nonparametric regression. The estimators for the regression coefficients are shown to be jointly root-n consistent and asymptotically normal. In addition, the estimator for the unknown regression function is a local linear kernel regression estimator and can be estimated with the same efficiency as all the parameters are known. Monte Carlo simulations are conducted to illustrate the proposed methodology.     

Boundary Value Problems for Ordinary Differential Equations with Deviated Arguments

We discuss differential equations with nonlinear boundary conditions. We formulate sufficient conditions under which problems with deviating arguments have quasisolutions or solutions. To obtain the results, we apply the method of monotone iterations.     

Local polynomial fitting under association

We consider the estimation of multivariate regression functions r(x₁,…,x_d) and their partial derivatives up to a total order p1 using high-order local polynomial fitting. The processes {Y_i,X_i} are assumed to be (jointly) associated. Joint asymptotic normality is established for the estimates of the regression function r and all its partial derivatives up to the total order p. Expressions for the bias and variance/covariance matrix (of the asymptotic distribution) are given.     

The double exponential map and covariant derivation

We study the double exponential map which is a composition of a special form of two exponential maps on a manifold with connection. We relate this map and the composition of covariant derivations as well as the composition of pseudodifferential operators on these manifolds.     

A geometric theory forL 2-stability of the inverse problem in a one-dimensional elliptic equation from anH 1-observation

This study provides a stability theory for the nonlinear least-squares formulation of estimating the diffusion coefficient in a two-point boundary-value problem from an error-corrupted observation of the state variable. It is based on analysing the projection of the observation on the nonconvex attainable set.This research was started while G. Chavent visited the Technical University of Graz. Support through the Steiermaerkische Landesregierung is gratefully acknowledged.     

BAHADUR ASYMPTOTIC EFFICIENCY IN A SEMIPARAMETRIC REGRESSION MODEL

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Gauge-invariant treatment of the exponential decay of an unstable atomic state

Summary By using a self-consistent projection-operator method, developed recently by the present author, a gauge-invariant Markovian treatment of the spontaneous decay of an unstable atomic state is presented. Without ignoring retardation and electron-spin effects a gauge-invariant result for the probability amplitude of finding the atom in the unstable state is obtained.