Decomposition of multi-exponential and related signals is generalized as an inverse filtering problem on a logarithmic time or frequency scale, and discrete-time filters operating with equally spaced data on a logarithmic scale (geometrically spaced on linear scale) are proposed for its implementation. Ideal prototypes, algorithms and types of filters are found for various timeand frequency-dom...

Linear mixed models (LMMs) are a powerful and established tool for studying genotype-phenotype relationships. A limiting assumption of LMMs is that the residuals are Gaussian distributed, a requirement that rarely holds in practice. Violations of this assumption can lead to false conclusions and losses in power, and hence it is common practice to pre-process the phenotypic values to make them G...

The balanced truncation method for reducing the size of a model was originally developed for linear systems. When extended to nonlinear systems, some considerationsmust be faced. First of all, the calculation of the balancing transformationmatrix is not unique. This may results in nonphysical values for the reconstructed states, which may lead to failure, for example, in thermodynamic routines....

Removing divergences in the negative moments of the multi-fractal partition function with the wavelet transformation ABSTRACT We present a promising technique which is capable of accessing the divergence free component of the partition function for the negative moments of the multi-fractal analysis of data using the wavelet transformation. It is based on implicitly bounding the local logarithmi...

Linear mixed models (LMMs) are a powerful and established tool for studying genotype-phenotype relationships. A limitation of the LMM is that the model assumes Gaussian distributed residuals, a requirement that rarely holds in practice. Violations of this assumption can lead to false conclusions and loss in power. To mitigate this problem, it is common practice to pre-process the phenotypic val...

Service systems such as call centers and hospital emergency rooms typically have strongly time-varying arrival rates. Thus, a nonhomogeneous Poisson process (NHPP) is a natural model for the arrival process in a queueing model for performance analysis. Nevertheless, it is important to perform statistical tests with service system data to confirm that an NHPP is actually appropriate, as emphasiz...

The most common pharmacokinetic responses of the rate and the extent of absorption are: Area under the plasma concentration-time curve (AUC), maximum plasma concentration (Cmax), and time to reach maximum plasma concentration (tmax). The distributions of responses such as AUC and Cmax are often positively skewed and exhibit a lack of homogeneity of variances. Therefore, normality assumption on ...

Data analysis is a quite important process and has been extensively employed in many areas. Especially in statistics, the distribution type test of data often needs to be handled. This paper presents that linear regression as a type of universal method can be applied to the distribution type test. In reliability engineering due to the failure data is commonly of non-linear relationship so that ...

Disjunctive logic programming (DLP) with stable model semantics is a powerful nonmonotonic formalism for knowledge representation and reasoning. Reasoning with DLP is harder than with normal (∨-free) logic programs; because stable model checking – deciding whether a given model is a stable model of a propositional DLP program – is co-NP-complete, while it is polynomial for normal logic programs...