Predictive developmental hypotheses play a crucial role in developmental theories. These hypotheses link early developmental behaviors or processes to later developmental outcomes. Empirical tests of predictive developmental hypotheses are generally based on standard regression models. It is argued that hierarchical linear models or longitudinal multilevel models offer a better alternative. A m...

We analyze the variability in the x-ray lightcurves of the black hole candidate Cygnus X-1 by linear and nonlinear time series analysis methods. While a linear model describes the overall second order properties of the observed data well, surrogate data analysis reveals a significant deviation from linearity. We discuss the relation between shot noise models usually applied to analyze these dat...

Inferring species interactions from co-occurrence data is one of the most controversial tasks in community ecology. One difficulty is that a single pairwise interaction can ripple through an ecological network and produce surprising indirect consequences. For example, the negative correlation between two competing species can be reversed in the presence of a third species that outcompetes both ...

This paper develops default priors for Bayesian analysis that reproduce familiar frequentist and Bayesian analyses for models that are exponential or location. For the vector parameter case there is an information adjustment that avoids the Bayesian marginalization paradoxes and properly targets the prior on the parameter of interest thus adjusting for any complicating nonlinearity the details ...

phenomenon of price manipulation is one of the factors which have caused mistrust of the investors to the stock market and inhibits its growth and prosperity. entering the shareholders into the stock market, on one hand leads to increase in the general level of revenues and on the other hand causes inexpensive financing for companies. in this research, at first by using duration dependence test...

A new method for testing linear restrictions in linear regression models is suggested. It allows to validate the linear restriction, up to a specified approximation error and with a specified error probability. The test relies on asymptotic normality of the test statistic, and therefore normality of the errors in the regression model is not required. In a simulation study the performance of the...