Penalized likelihood approach for the four-parameter kappa distribution

The four-parameter kappa distribution (K4D) is a generalized form of some commonly used distributions such as generalized logistic, generalized Pareto, generalized Gumbel, and generalized extreme value (GEV) distributions. Owing to its flexibility, the K4D is widely applied in modeling in several fields such as hydrology and climatic change. For the estimation of the four parameters, the maximum likelihood approach and the method of L-moments are usually employed. The L-moment estimator (LME) method works well for some parameter spaces, with up to a moderate sample size, but it is sometimes not feasible in terms of computing the appropriate estimates. Meanwhile, using the maximum likelihood estimator (MLE) with small sample sizes shows substantially poor performance in terms of a large variance of the estimator. We therefore propose a maximum penalized likelihood estimation (MPLE) of K4D by adjusting the existing penalty functions that restrict the parameter space. Eighteen combinations of penalties for two shape parameters are considered and compared. The MPLE retains modeling flexibility and large sample optimality while also improving on small sample properties. The properties of the proposed estimator are verified through a Monte Carlo simulation, and an application case is demonstrated taking Thailand’s annual maximum temperature data.     

The Motivational Interpretation of Institutions

Lorsqu'on distingue la motivation de rle de la motivation personnelle sentie, les institutions humaines peuvent ětre analysées sans que l'analyse soit liée a une explication psychologique ou structurelle. La position de ≪ l'individualisme méthodologique ≫ si souvent préconisée par Homans embrouille, à notre point de vue, I'étude des institutions. Pour autant le sociologisme n'est pas un choix forcé. Les relations entre la structure et le sentiment sont seulement brouillées lorsqu'on identifie ≪ structure ≫ et ≪ autorité≫ et lorsqu'on considère que la charge émotive est synonyme de conduite non-structurée. Dans les deux cas, la coloration motivationnelle d'une relation de rôle est une partie du modèle particulier de l'institution.
When role motivation is distinguished from sentient and personal motivation, human institutions are subject to a kind of analysis which is bound neither to psychological nor structural explanation. The position of "methodological individualism," which Homans has argued at length, can be shown to confuse the study of institutions. But sociologism is not for that reason a forced choice. The relations of structure and sentiment are only confused where "authority" is identified with "structure" and positive effect considered to be unstructured behaviour. The motivational colouration of a role-relationship in either case is part of the given pattern of the institution.     

A parametric approach for measuring the effect of the 10th revision of the international classification of diseases

Summary.  The World Health Organization revises the international classification of diseases about every 10 years to stay abreast of advances in medical science and to compare international health statistics. However, the new revision (i.e. the 10th revision) introduces discontinuities in mortality trends, making it impossible to compare the mortality statistics before and after the revision directly. The US National Center for Health Statistics published comparability ratios to correct the discontinuities between the two sets of mortality data: one coded by the ninth revision and the other by the 10th revision. We propose a parametric two-stage model to produce new comparability ratios and use these ratios to correct the discontinuities. The asymptotic behaviour of the comparability ratios is investigated. Our model not only measures the extent of discontinuities in trends in mortality but also can be used to forecast future mortality. Comparing with the National Center for Health Statistics's ratios, our comparability ratios smooth out the discontinuities better for most causes.     

Estimating the immigration multiplier: an analysis of recent Korean and Filipino immigration to the United States

"This article explores the effect of 'chaining' through the petitioning of relatives on the demand for future immigrant visas [to the United States]. The data for the study come from a 1986 survey of 3,911 respondents from the Philippines and the Republic of Korea who were interviewed in Manila and Seoul just after they had received their U.S. immigrant visas. Analyses are conducted to derive different types of multipliers that may be used in estimating the effects of chain migration.... The empirical results for the Philippines and Korea indicate that the potential for future immigration through the family reunification entitlements of the immigration law is lower than has previously been suggested." This is a revised version of a paper originally presented at the 1987 Annual Meeting of the Population Association of America (see Population Index, Vol. 53, No. 3, Fall 1987, p. 385).     

Exploring an analytic model of urban housing strata

An analytic model of urban housing strata is developed which utilizes housing structure type, housing tenure type, floor size, physical quality, residential area, and number of rooms to calculate a housing deficit for each housing characteristic. The housing norm is subtracted from the actual housing conditions. Each housing deficit value is weighted according to the priority of the 6 variables and then summed as the housing strata score. Negative scores are below the norm and positive ones above. The model is applied to empirical data for Seoul, Korea. The findings were that 66% of the family sample showed negative scores (unsatisfactory housing conditions). Scores range from -22 to =or+ 18. Morris and Winter's "housing adjustment model" is used to explain housing behavior when there is a gap between housing conditions and the norm. Housing behavior is analyzed with multiple regression analysis of housing strata, social strata, and family life stage variables. Findings indicate that the establishment stage in the family life cycle is more likely to be associated with upper housing strata. From the way the model is set up only those in the establishment, childbearing, and child-rearing stage could get a positive deficit housing score. Size of household is not statistically significant, but upper housing strata are reflective of families with 2.5 members. Those with 3-4.5 members may be in the upper middle housing strata. Those with 5 children are in the lower middle housing strata. Housing strata are significantly related to housing structure type, tenure type, and size and number of rooms. The high rise apartment is likely to be in the upper, the row house and multifamily house in the lower housing, and the single detached house is distributed through all 4 strata. Home ownership is highest in the upper strata. The proportion of housing with 18 pyong and 2 rooms is higher in the lower strata, while housing with 19-32 pyong (63-106 sq. ms) and 3 rooms is higher in the middle housing strata. Housing satisfaction is significantly explained by housing strata but not general social strata (r = .13). Propensity to move is explained by family life stage followed by housing strata.     

Relationship building and the use of Web sites: How Fortune 500 corporations use their Web sites to build relationships

This study examines the dialogic features of corporate Web sites in order to determine the Web site practices of the corporations for building relationships with their publics. Content analysis of 100 Fortune 500 companies’ Web sites revealed that the corporations designed their Web sites to serve important publics and foster dialogic communication. The corporate Web sites appear to promote control mutuality, trust, satisfaction, openness, and intimacy. However, the corporations need to maintain repetitive interactions with their publics to enhance trust, commitment, and exchange relationship.     

Censored time series analysis with autoregressive moving average models

The authors consider time series observations with data irregularities such as censoring due to a detection limit. Practitioners commonly disregard censored data cases which often result in biased estimates. The authors present an attractive remedy for handling autocorrelated censored data based on a class of autoregressive and moving average (ARMA) models. In particular, they introduce an imputation method well suited for fitting ARMA models in the presence of censored data. They demonstrate the effectiveness of their technique in terms of bias, efficiency, and information loss. They also describe its adaptation to a specific context of meteorological time series data on cloud ceiling height, which are measured subject to the detection limit of the recording device.