Based on the probabilistic reformulation of principal component analysis (PCA), we consider the problem of determining the number of principal components as a model selection problem. We present a hierarchical model for probabilistic PCA and construct a Bayesian inference method for this model using reversible jump Markov chain Monte Carlo (MCMC). By regarding each principal component as a poin...

Large number of studies showed that landing with great impact forces may be a risk factor for knee injuries. The purpose of this study was to illustrate the different landing loads to lower extremity of both genders and examine the relationships among selected lower extremity kinematics and kinetics during the landing of a stop-jump task. A total of 35 male and 35 female healthy subjects were r...

Large stock price movements are modeled as jumps in the stochastic processes of stock prices. In the current literature, the jump intensity is typically specified in models as a function of the current diffusive volatility and past jump intensities, while the jump size is assumed to be independent of the jump intensity. We use a nonparametric jump detection test to identify jumps in several sto...

Many recent modelling advances in …nance topics ranging from the pricing of volatility-based derivative products to asset management are predicated on the importance of jumps, or discontinuous movements in asset returns. In light of this, a number of recent papers have addressed volatility predictability, some from the perspective of the usefulness of jumps in forecasting volatility. Key papers...

We study the origin of the bi-stability jump in the terminal velocity of the winds of supergiants near spectral type B1. Observations show that here the ratio v∞/vesc drops steeply from about 2.6 at types earlier than B1 to a value of v∞/vesc=1.3 at types later than B2. To this purpose, we have calculated wind models and mass-loss rates for early-type supergiants in a Teff grid covering the ran...

This paper is devoted the the study of the mean field limit for many-particle systems undergoing jump, drift or diffusion processes, as well as combinations of them. The main results are quantitative estimates on the decay of fluctuations around the deterministic limit and of correlations between particles, as the number of particles goes to infinity. To this end we introduce a general function...

PURPOSE The number of familiarization sessions in fitness assessments seems to be critical and inconsistent. Therefore, the primary aim of this research was to determine the number of familiarization attempts that stabilize the results in particular physical fitness tests. The secondary aim was to establish the test reliability through familiarization sessions. METHODS Thirty-nine primary sch...

The Bounded Diameter Minimum Spanning Tree problem (BDMST) and the Hop Constrained Minimum Spanning Tree problems (HCMST) are NP-hard combinatorial optimization problems which have their main application in network design. In this thesis an existing relax-and-cut approach for finding lower bounds and approximate solutions to those problems is enhanced and extended, and a hybrid algorithm based ...

We present a novel approach to inference in conditionally Gaussian continuous time stochastic processes, where the latent process is a Markovian jump process. We first consider the case of jump-diffusion processes, where the drift of a linear stochastic differential equation can jump at arbitrary time points. We derive partial differential equations for exact inference and present a very effici...

We consider the problem of finding optimal “jumping” patterns from 1 to N where there is a cost associated with each jump. This will be done for two cost functions, in the first case the cost of jumping from a to b will be (1 − q)/a for 0 < q < 1, while the second cost function will be b/a. For the first cost function we will show that all the jump lengths, except possibly the last jump, are be...