Symbolic reduction of block diagrams using FORMAC

Two computer programs - one written in FORMAC to generate the desired symbolic expressions, the other in FORTRAN 4 to numerically evaluate the expressions are announced. The FORTRAN program accepts the symbolic punched output from the FORMAC program in either unexpanded or expanded form. It numerically evaluates the expressions

On Nilcompactifications of Prime Spectra of Commutative Rings

Given a ring R and S one of its ideals, we obtain a compactification of the prime spectrum of S through a mainly algebraic process. We name it the R-nilcompactification of SpecS. We study some categorical properties of this construction.Comment: 12 pages, 8 Tikz figure

Distributed Adaptive Learning of Graph Signals

The aim of this paper is to propose distributed strategies for adaptive learning of signals defined over graphs. Assuming the graph signal to be bandlimited, the method enables distributed reconstruction, with guaranteed performance in terms of mean-square error, and tracking from a limited number of sampled observations taken from a subset of vertices. A detailed mean square analysis is carried out and illustrates the role played by the sampling strategy on the performance of the proposed method. Finally, some useful strategies for distributed selection of the sampling set are provided. Several numerical results validate our theoretical findings, and illustrate the performance of the proposed method for distributed adaptive learning of signals defined over graphs.Comment: To appear in IEEE Transactions on Signal Processing, 201

Multivariate probit regression using simulated maximum likelihood

We discuss the application of the GHK simulation method to maximum likelihood estimation of the multivariate probit regression model, and describe and illustrate a Stata program mvprobit for this purpose.

The Dynamics of Social Assistance Benefit Receipt in Britain

We analyze the dynamics of social assistance benefit (SA) receipt among working-age adults in Britain between 1991 and 2005. The decline in the annual SA receipt rate was driven by a decline in the SA entry rate, rather than by the SA exit rate (which actually declined too). We examine the determinants of these trends using a multivariate dynamic random effects probit model of SA entry and exit probabilities applied to British Household Panel Survey data. The model estimates and accompanying counterfactual simulations highlight the importance of two factors – the decline in the unemployment rate over the period, and other changes in the socioeconomic environment including two reforms to the income maintenance system in the 1990s. The results also reveal a substantial heterogeneity in SA annual transition rates.benefits, income dynamics, social assistance, welfare, dynamic random effects probit

Modelling Low Pay Transition Probabilities, Accounting for Panel Attrition, Non-Response, and Initial Conditions

We model annual low pay transition probabilities taking account of three potentially endogenous selections: two sample drop-out mechanisms (panel attrition, non-employment) and ‘initial conditions’ (base-year low pay status). This model, and variants that ignore one or more of these selection mechanisms, are fitted to data for men from the British Household Panel Survey. Tests of the ignorability of the endogenous selection mechanisms suggest that ‘economic’ selection mechanisms such as initial conditions and retention of employment are more important than the ‘survey’ selection mechanism (attrition). However, consistent with related US research, relatively simple models provide estimates of covariate effects that differ little from the estimates from the complicated models.transition probabilities, low pay, attrition, non-response, ignorability

Calculation of Multivariate Normal Probabilities by Simulation, with Applications to Maximum Simulated Likelihood Estimation

We discuss methods for calculating multivariate normal probabilities by simulation and two new Stata programs for this purpose: mvdraws for deriving draws from the standard uniform density using either Halton or pseudo-random sequences, and an egen function mvnp() for calculating the probabilities themselves. Several illustrations show how the programs may be used for maximum simulated likelihood estimation.Simulation estimation, maximum simulated likelihood, multivariate probit, Halton sequences, pseudo-random sequences, multivariate normal, GHK simulator

The Dynamics of Social Assistance Receipt: Measurement and Modelling Issues, with an Application to Britain

We model the dynamics of social assistance benefit receipt in Britain using data from the British Household Panel Survey, waves 1–15. First, we discuss definitions of social assistance benefit receipt, and present information about the trends between 1991 and 2005 in the receipt of social assistance benefits, and in annual rates of transition into and out of receipt. Second, we review potential multivariate modelling approaches especially the dynamic random effects probit models that are used in our empirical analysis and, third, discuss sample selection criteria and explanatory variables. Fourth, we present our regression estimation estimates and interpret them. The final section contains a summary of the substantive results, and highlights some lessons concerning application of the analysis for other countries and some methodological issues.social assistance, welfare benefits, dynamic random effects probit, income dynamics

The dynamics of social assistance receipt: measurement and modelling issues, with an application to Britain

We model the dynamics of social assistance benefit receipt in Britain using data from the British Household Panel Survey, waves 1–15. First, we discuss definitions of social assistance benefit receipt, and present information about the trends between 1991 and 2005 in the receipt of social assistance benefits, and in annual rates of transition into and out of receipt. Second, we review potential multivariate modelling approaches especially the dynamic random effects probit models that are used in our empirical analysis and, third, discuss sample selection criteria and explanatory variables. Fourth, we present our regression estimation estimates and interpret them. The final section contains a summary of the substantive results, and highlights some lessons concerning application of the analysis for other countries and some methodological issues.social assistance, benefit dynamics, income dynamics, dynamic random effects probit, British Household Panel Survey