A Bayesian meta-analysis of infants’ ability to perceive audio–visual congruence for speech

This paper quantifies the extent to which infants can perceive audio–visual congruence for speech information and assesses whether this ability changes with native language exposure over time. A hierarchical Bayesian robust regression model of 92 separate effect sizes extracted from 24 studies indicates a moderate effect size in a positive direction (0.35, CI [0.21: 0.50]). This result suggests that infants possess a robust ability to detect audio–visual congruence for speech. Moderator analyses, moreover, suggest that infants’ audio–visual matching ability for speech emerges at an early point in the process of language acquisition and remains stable for both native and non-native speech throughout early development. A sensitivity analysis of the meta-analytic data, however, indicates that a moderate publication bias for significant results could shift the lower credible interval to include null effects. Based on these findings, we outline recommendations for new lines of enquiry and suggest ways to improve the replicability of results in future investigations.     

Introducing LASSO-type penalisation to generalised joint regression modelling for count data

AStA Advances in Statistical Analysis - In this work, we propose an extension of the versatile joint regression framework for bivariate count responses of the R package GJRM by Marra and Radice (R...     

A new approach to choose acceptance cutoff for approximate Bayesian computation

The approximate Bayesian computation (ABC) algorithm is used to estimate parameters from complicated phenomena, where likelihood is intractable. Here, we report the development of an algorithm to choose the tolerance level for ABC. We have illustrated the performance of our proposed method by simulating the estimation of scaled mutation and recombination rates. The result shows that the proposed algorithm performs well.     

Shortest and longest length of success runs in binary sequences

The shortest and the longest length of success runs statistics in binary sequences are considered. The sequences are arranged on a line or on a circle. Exact probabilities of these statistics are derived, both in closed formulae via combinatorial analysis, as well as recursively. Furthermore, their joint probability distribution function and cumulative distribution function are obtained. The results are developed first for Bernoulli trials (i.i.d. binary sequences), and then they are generalized to the Polya–Eggenberger sampling scheme. For the latter case, the length of the longest success run is related to other success runs statistics and to reliability of consecutive systems.     

Innovation and Sectoral Employment: A Trade–off between Compensation Mechanisms

The question whether technological progress displaces employment or whether technological advance is beneficial for the level of employment has been at the core of economic debate for over two centuries. The beneficial effect might be achieved by several compensation mechanisms within the economic system. In this paper we categorize these compensation mechanisms into two basic categories that reflect the different nature of the ideas ruling the compensation. We discriminate the mechanisms of employment despite innovation from employment via innovation. In the context of new innovation economics we model an artificial industry implementing both compensation mechanisms. Simulation analysis is used to examine both the short–run and long–run properties of the model. There we focus on the influence of wage restraint policy on the functioning of the compensation mechanism.     

Interactive Job Shop Scheduling: An Experiment

An experiment is discussed in which three computer-aided, interactive job shop scheduling approaches are compared using an interactive job shop scheduling simulator (JOB) developed for the project. All three approaches use a combination of computer and human capabilities to develop job shop schedules, but differ in terms of the timing and degree of human involvement required. The three scheduling approaches are (1) the successive approach, (2) the interactive approach, and (3) the semi-interactive approach. The successive approach is characterized by the computer scheduling all work orders without any human intervention. The interactive approach is distinguished by the human scheduling one work order at a time until all work orders are scheduled. The schedule is developed interactively by the person who must simultaneously consider work-order scheduling needs and machine group load capacities. The semi-interactive approach may be viewed as a combination of the successive and interactive approaches. Work orders are automatically scheduled one at a time using the successive approach criteria, but with prespecified machine-group load thresholds. As long as the load threshold is not exceeded, the successive approach is used to schedule work orders. When a threshold is exceeded, the algorithm (successive approach) pauses and human rescheduling (interactive approach) is required to rectify the overload situation. A second (reallocation) phase, identical for all three approaches, is used to overcome any scheduling problems generated in phase one. Experimental results based on nine different performance criteria (including scheduling time, makespan, machine group utilization, and work-in-process inventory) and 45 experimental runs indicate that there are differences between the results produced by the three scheduling approaches. The interactive approach yields the best overall scheduling results, but the other two approaches are clearly better than the interactive approach in some situations. The success of the interactive approach indicates that it is usually best for the human scheduler to become involved early in the computer-based job shop scheduling process.     

A SIMULATION STUDY OF DECENTRALIZED DECISION MAKING*

This study develops a heuristic procedure for decision making coordination in a decentralized organization structure. The procedure consists of simplified rules of iterative communication between decentralized units and a central agent. The central agent assigns budgeted profit levels and adjusts such levels guiding the system toward optimality. The decision making procedure developed in this study is compatible with management by objectives practices and can serve as a prototype for decentralized management.