In phylogenetic analyses of molecular sequence data, partitioning involves estimating independent models of molecular evolution for different sets of sites in a sequence alignment. Choosing an appropriate partitioning scheme is an important step in most analyses because it can affect the accuracy of phylogenetic reconstruction. Despite this, partitioning schemes are often chosen without explici...

This paper presents an empirical mode decomposition (EMD) based adaptive filter (AF) for channel estimation in OFDM system.  In this method, length of channel impulse response (CIR) is first approximated using Akaike information criterion (AIC). Then, CIR is estimated using adaptive filter with EMD decomposed IMF of the received OFDM symbol. The correlation and kurtosis measures are used to sel...

Evolutionary biologists have long been fascinated by the extreme differences in species numbers across branches of the Tree of Life. This has motivated the development of statistical methods for detecting shifts in the rate of lineage diversification across the branches of phylogenic trees. One of the most frequently used methods, MEDUSA, explores a set of diversification-rate models, where eac...

Identification of chemical reaction processes in subsurface environments is a key issue for reactive transport modeling because simulating different processes requires developing different chemical–mathematical models. In this paper, two sorption processes (equilibrium and kinetics) are considered for modeling neptunium and uranium sorption in fractured rock. Based on different conceptualizatio...

Model selection is a central component of data analysis Though there are a variety of methods for likelihood based estimation methods there are relatively few for non likelihood based generalized linear models GLM such as in the quasi likelihood and generalized es timating equation GEE approaches In this paper we develop basic and bias corrected bootstrap approaches to estimate the predictive m...

The study presents an algorithm, ParSCAPE, for model-independent extraction of peak positions and intensities from atomic pair distribution functions (PDFs). It provides a statistically motivated method for determining parsimony of extracted peak models using the information-theoretic Akaike information criterion (AIC) applied to plausible models generated within an iterative framework of clust...

The purpose of this paper is to predict the lending interest rate and deposit Bangladesh using Autoregressive Integrated Moving Average (ARIMA) model by Box Jenkins. It has been found that ARIMA (1, 0, 1) appropriate in predicting both rates from 2022 2026 data presented World Bank Open Data 1976 2021. To test goodness fit, AIC (Akaike Information Criterion) BIC (Bayesian index values have calc...