Two step estimation for Neyman-Scott point process with inhomogeneous cluster centers

This paper is concerned with parameter estimation for the Neyman-Scott point process with inhomogeneous cluster centers. Inhomogeneity depends on spatial covariates. The regression parameters are estimated at the first step using a Poisson likelihood score function. Three estimation procedures (minimum contrast method based on a modified K function, composite likelihood and Bayesian methods) are introduced for estimation of clustering parameters at the second step. The performance of the estimation methods are studied and compared via a simulation study. This work has been motivated and illustrated by ecological studies of fish spatial distribution in an inland reservoir.     

Omnibus tests for the error distribution in the linear regression model

Test procedures are constructed for testing the goodness-of-fit of the error distribution in the regression context. The test statistic is based on an L ²-type distance between the characteristic function of the (assumed) error distribution and the empirical characteristic function of the residuals. The asymptotic null distribution as well as the behavior of the test statistic under contiguous alternatives is investigated, while the issue of the choice of suitable estimators has been particularly emphasized. Theoretical results are accompanied by a simulation study.     

Border estimation of a two-dimensional uniform distribution if data are measured with additive error

The paper considers estimation of the boundary of an elliptical domain when the data without a measurement error are distributed uniformly on this domain but are superimposed by random errors. The problem is solved in two phases. In the first phase the domain is subdivided into thin slices and the endpoints of these slices are estimated within the framework of a corresponding one-dimensional problem. In the second phase the estimated endpoints are used to estimate the boundary using the total least-squares curve fitting procedure.     

Total least squares and bootstrapping with applications in calibration

The solution to the errors-in-variables problem computed through total least squares is highly nonlinear. Because of this, many statistical procedures for constructing confidence intervals and testing hypotheses cannot be applied. One possible solution to this dilemma is bootstrapping. A nonparametric bootstrap technique could fail. Here, the proper nonparametric bootstrap procedure is provided and its correctness is proved. On the other hand, a residual bootstrap is not valid and suitable in this case. The results are illustrated through a simulation study. An application of this approach to calibration data is presented.     

Self-weighted recursive estimation of GARCH models

The generalized autoregressive conditional heteroscedasticity (GARCH) processes are frequently used to investigate and model financial returns. They are routinely estimated by computationally complex off-line estimation methods, for example, by the conditional maximum likelihood procedure. However, in many empirical applications (especially in the context of high-frequency financial data), it seems necessary to apply numerically more effective techniques to calibrate and monitor such models. The aims of this contribution are: (i) to review the previously introduced recursive estimation algorithms and to derive self-weighted alternatives applying general recursive identification instruments, and (ii) to examine these methods by means of simulations and an empirical application.     

Attachment Perspective on Marital Dissolution and Relational Family Therapy

Divorce or dissolution of a long-term intimate relationship is an event on the continuum of an individual’s experience of attachment injury that is reawakened and played out again in this process. An attachment injury means the experience of rejection and betrayal of trust at a critical time of distress when one is in need of support. By means of the case study method, the article presents a case of a female client dealing with divorce. The history of traumatic relations through a lens of attachment theory is presented, along with divorce as the reawakening of an attachment injury and its processing in a relational family therapy model.     

Causes of Divorce from the Perspective of Females in Slovenia

Divorce is a stressful life transition and does not have a single cause. This article presents the results of qualitative research on the causes for separation as perceived by women in Slovenia. Ten interviews were carried out with women divorced for less than 10 years and between 29 and 57 years old. The women created their own meanings of the reasons for divorce, all of which corresponded with other studies. The findings confirm the complex factors that contribute to the disintegration of marriage and that existed prior to the divorce. The research results present a vantage point for developing preventive activities that foster improved quality of interpersonal relationships in Slovenia.