Small‐sample testing inference in symmetric and log‐symmetric linear regression models

This paper deals with the issue of testing hypotheses in symmetric and log‐symmetric linear regression models in small and moderate‐sized samples. We focus on four tests, namely, the Wald, likelihood ratio, score, and gradient tests. These tests rely on asymptotic results and are unreliable when the sample size is not large enough to guarantee a good agreement between the exact distribution of the test statistic and the corresponding chi‐squared asymptotic distribution. Bartlett and Bartlett‐type corrections typically attenuate the size distortion of the tests. These corrections are available in the literature for the likelihood ratio and score tests in symmetric linear regression models. Here, we derive a Bartlett‐type correction for the gradient test. We show that the corrections are also valid for the log‐symmetric linear regression models. We numerically compare the various tests and bootstrapped tests, through simulations. Our results suggest that the corrected and bootstrapped tests exhibit type I probability error closer to the chosen nominal level with virtually no power loss. The analytically corrected tests as well as the bootstrapped tests, including the Bartlett‐corrected gradient test derived in this paper, perform with the advantage of not requiring computationally intensive calculations. We present a real data application to illustrate the usefulness of the modified tests.     

Rank tests for testing randomness of a regression coefficient in a linear regression model

We propose a class of nonparametric tests for testing non-stochasticity of the regression parameterβ in the regression modely _i =βx _i +ɛ _i ,i=1, ...,n. We prove that the test statistics are asymptotically normally distributed both underH ₀ and under contiguous alternatives. The asymptotic relative efficiencies (in the Pitman sense) with respect to the best parametric test have also been computed and they are quite high. Some simulation studies are carried out to illustrate the results. Research was supported by the University Grants Commission, India.     

Investigating the impact of excess zeros on hurdle‐generalized Poisson regression model with right censored count data

Typically, a Poisson model is assumed for count data. In many cases, there are many zeros in the dependent variable, thus the mean is not equal to the variance value of the dependent variable. Therefore, Poisson model is not suitable anymore for this kind of data because of too many zeros. Thus, we suggest using a hurdle‐generalized Poisson regression model. Furthermore, the response variable in such cases is censored for some values because of some big values. A censored hurdle‐generalized Poisson regression model is introduced on count data with many zeros in this paper. The estimation of regression parameters using the maximum likelihood method is discussed and the goodness‐of‐fit for the regression model is examined. An example and a simulation will be used to illustrate the effects of right censoring on the parameter estimation and their standard errors.     

Asymptotic results and tests for the choice of approximative models in nonlinear two-phases regression models, heteroscedatic case

This paper is devoted to the study of the least squares estimator of f for the classical, fixed design, nonlinear model X (t _i)=f(t _i)+ε(t _i), i=1,2,…,n, where the (ε(t _i))_i=1,…,n are independent second order r.v.. The estimation of f is based upon a given parametric form. In Brodeau (1993) this subject has been studied in the homoscedastic case. This time we assume that the ε(t _i) have non constant and unknown variances σ²(t _i). Our main goal is to develop two statistical tests, one for testing that f belongs to a given class of functions possibly discontinuous in their first derivative, and another for comparing two such classes. The fundamental tool is an approximation of the elements of these classes by more regular functions, which leads to asymptotic properties of estimators based on the least squares estimator of the unknown parameters. We point out that Neubauer and Zwanzig (1995) have obtained interesting results for connected subjects by using the same technique of approximation. Received: February 1996     

Bayesian regression with B‐splines under combinations of shape constraints and smoothness properties

In this paper, we approach the problem of shape constrained regression from a Bayesian perspective. A B‐splines basis is used to model the regression function. The smoothness of the regression function is controlled by the order of the B‐splines, and the shape is controlled by the shape of an associated control polygon. Controlling the shape of the control polygon reduces to some inequality constraints on the spline coefficients. Our approach enables us to take into account combinations of shape constraints and to localize each shape constraint on a given interval. The performance of our method is investigated through a simulation study. Applications to a real data sets in food industry and Global Warming are provided.     

A bivariate infinitely divisible law for modeling the magnitude and duration of monotone periods of log‐returns

The focus of this article is modeling the magnitude and duration of monotone periods of log‐returns. For this, we propose a new bivariate law assuming that the probabilistic framework over the magnitude and duration is based on the joint distribution of (X,N), where N is geometric distributed and X is the sum of an identically distributed sequence of inverse‐Gaussian random variables independent of N. In this sense, X and N represent the magnitude and duration of the log‐returns, respectively, and the magnitude comes from an infinite mixture of inverse‐Gaussian distributions. This new model is named bivariate inverse‐Gaussian geometric ( in short) law. We provide statistical properties of the model and explore stochastic representations. In particular, we show that the is infinitely divisible, and with this, an induced Lévy process is proposed and studied in some detail. Estimation of the parameters is performed via maximum likelihood, and Fisher's information matrix is obtained. An empirical illustration to the log‐returns of Tyco International stock demonstrates the superior performance of the law compared to an existing model. We expect that the proposed law can be considered as a powerful tool in the modeling of log‐returns and other episodes analyses such as water resources management, risk assessment, and civil engineering projects.     

Minimax‐Optimal Strength of Statistical Evidence for a Composite Alternative Hypothesis

While the likelihood ratio measures statistical support for an alternative hypothesis about a single parameter value, it is undefined for an alternative hypothesis that is composite in the sense that it corresponds to multiple parameter values. Regarding the parameter of interest as a random variable enables measuring support for a composite alternative hypothesis without requiring the elicitation or estimation of a prior distribution, as described below. In this setting, in which parameter randomness represents variability rather than uncertainty, the ideal measure of the support for one hypothesis over another is the difference in the posterior and prior log‐odds. That ideal support may be replaced by any measure of support that, on a per‐observation basis, is asymptotically unbiased as a predictor of the ideal support. Such measures of support are easily interpreted and, if desired, can be combined with any specified or estimated prior probability of the null hypothesis. Two qualifying measures of support are minimax‐optimal. An application to proteomics data indicates that a modification of optimal support computed from data for a single protein can closely approximate the estimated difference in posterior and prior odds that would be available with the data for 20 proteins.     

Legal Technologies of Primitive Accumulation: Judicial Robbery and Dispossession‐by‐Restitution in Warsaw

Among the ‘extra‐economic means’ that facilitate primitive accumulation, or accumulation by dispossession, the law plays a prominent role. But works on neoliberal urban restructuring rarely engage with concrete legal technologies. Analysing judicial property restitution (‘reprivatization’) in Warsaw, this article grasps the machine of accumulation by dispossession at a moment of faltering and exposes the distinctive legal technologies behind its troubleshooting. It makes three contributions to critical urban studies. First, it demonstrates how judicial systems can steal political conflicts that obstruct the cycle of accumulation by dispossession. It thus introduces the notion of ‘judicial robbery’, a non‐legislated expropriation of common property through judicial engineering that simultaneously deprives the public of political agency. Second, it shows that seemingly neutral legal technicalities, usually sheltered from political debate, can become a key locus of urban politics. Third, it examines the agency, scope and spatial patterns of ‘dispossession by restitution’, the term I use for a locally specific form of accumulation by dispossession in Warsaw. Lastly, I raise the question of political struggle against primitive accumulation. Is the judicial robbery reversible? If we can reclaim property, can we also reclaim political conflicts that have been stolen by the law?     

Everybody Knows This is Nowhere: The Kiev Park of Memory and Post‐Soviet Urbanism in Context

The reappraisal of the post‐Soviet landscape is in danger of overlooking two of its most important elements: firstly, the mass modernist housing that was more extensive here than probably anywhere else; and secondly, the post‐1989 capitalist context of property speculation, office development and decay. These routinely missed landscapes constitute the very things travelled through on the way to utopian, if ruined, monuments, such as those documented in Frédéric Chaubin's CCCP — Cosmic Communist Constructions Photographed. When visited, the surroundings of these structures turn out to be at least as interesting as the photogenic modernist monument itself. This essay is an account of a visit to one of the most architecturally contemporary of these structures — the Park of Memory crematoria in the Ukrainian capital, Kiev, designed by Abraham Miletsky in 1974. In Chaubin's photographs, the curling concrete volumes of the Park's central crematoria are flamboyant, fantastical and self‐referential, the very ‘iconic’ architecture that many post‐Soviet capitals would like to have in order to attract tourists. There is a lot more going on in the surrounding city than what is typically recorded in its visual representations, however, as discussed in this essay. Such monuments are not mute, and cannot be severed from their surroundings.     

The influence of calculative (“hard”) and collaborative (“soft”) HRM on the layoff‐performance relationship in high performance workplaces

We investigate the effect of employment systems on the layoff‐performance relationship. We construct a typology of two types of HPWS (Calculative or “hard” HRM and Collaborative or “soft” HRM) and two non‐high performance systems (Traditional HRM and Low HRM). We use attribution theory as a framework from which to draw hypotheses. We examine survey responses from two waves of panel data. We employ cluster analysis to identify distinctive configurations of employment practices used in UK workplaces. We use the cluster outcomes as explanatory variables in moderator regression analysis. Following layoffs, we find that Calculative workplaces experience lower subsequent performance than Collaborative workplaces. Over the next five years, Calculative and Collaborative workplaces experience equivalent amounts of performance change but Calculative workplaces fail to make a full recovery.     

How Culture and Economy Meet in South Korea: The Politics of Cultural Economy in Culture‐led Urban Regeneration

This article investigates the ways in which cultural economy is formed through negotiation and interaction between local actors in the case of culture‐led regeneration in Gwangju, South Korea. It looks at the dynamics between the bureaucrats' pursuit of economic growth in the city and the efforts of civil society to maintain a strong political spirit throughout the regeneration process. Through in‐depth interviews with various participants and archival analysis, the politics of cultural economy are examined in relation to the Gwangju Biennale and the City of Culture project. The findings show that in these two cases bureaucrats were the dominant force, a tendency that instrumentalized culture. They also illustrate that this dominance brought about resistance from civil society. However, in the process of both engaging in conflict and working with each other, the different discourses of economic growth and cultural meaning were integrated, and in the process mutual learning and adaptation took place among members of the two groups. Civil society also faced cleavages resulting from different approaches to how to collaborate with the bureaucrats and its ensuing self‐reflection on communicative value enhanced its rehabilitation. The article argues that the politics of cultural economy is dynamic, involving processes of renegotiation, adaptation and self‐realization. It also offers the possibility of a new arena for the public sphere. Civil society plays a critical role in the integration of culture and economy.