We address an original statistical method for unsupervised identification and concentration estimation of spectrally interfering gas components of unknown nature and number. We show that such spectral unmixing can be efficiently achieved using information criteria derived from the Minimum Description Length (MDL) principle, outperforming standard information criteria such as AICc or BIC. In the...

The estimation of mixture models has been proposed for quite some time as an approach for cluster analysis. Several variants of the Expectation-Maximization algorithm are currently available for this purpose. Estimation of mixture models simultaneously allows the determination of the number of clusters and yields distributional parameters for clustering base variables. There are several informa...

GARCH model has gained popularity during the last two decades, because of their ability to capture non-linear dynamics in the real life data which we often observe especially in financial markets. This paper discuss four common information criteria (AIC, AICc, BIC and HQ) and their ability of correct selection in the presence of GARCH effect, based on their probability of correct selection as a...

The consequences of Maternal Mortality (MM) cannot be overemphasized. It inhibits population growth resulting into loss of lives among others. This work tends to obtain the maternal mortality rates (MMR) in Nigeria, identify some fitted distributions to MMR and determine which of the distributions best fits the data. A comprehensive Exploratory Data Analysis (EDA) was carried on MM and the MMRs...

This paper investigates the usefulness of information criteria for inference on the number of structural breaks in a standard linear regression model. In particular, we propose a modified penalty function for such criteria based on theoretical arguments, which implies each break is equivalent to estimation of three individual regression coefficients. A Monte Carlo analysis compares information ...

The paper obtains analytical results for the asymptotic properties of Model Selection Criteria – widely used in practice a general family hidden Markov models (HMMs), thereby substantially extending related theory beyond typical ‘i.i.d.-like’ model structures and filling an important gap relevant literature. In particular, we look at Bayesian Akaike Information (BIC AIC) evidence. setting neste...

BACKGROUND Independent Component Analysis (ICA) has been widely applied to the analysis of fMRI data. Accurate estimation of the number of independent components of fMRI data is critical to reduce over/under fitting. Although various methods based on Information Theoretic Criteria (ITC) have been used to estimate the intrinsic dimension of fMRI data, the relative performance of different ITC in...

The localization of oocyte-specific determinants in the form of mRNAs to the pro-oocyte is essential for the establishment of oocyte identity. Localization of the Bicaudal-D (Bic-D) protein to the presumptive oocyte is required for the accumulation of Bic-D and other mRNAs to the pro-oocyte. The Bic-D protein contains four well-defined heptad repeat domains characteristic of intermediate filame...

OBJECTIVE This article aims to describe the characteristics of the binaural interaction component (BIC) of speech-evoked auditory brainstem response (ABR). MATERIALS AND METHODS All 15 subjects had normal peripheral hearing sensitivity. ABRs were elicited by speech stimulus /da/. RESULTS The first BIC (BIC-SP1) in the speech-evoked ABR occurred at around 6 ms in the region of peak V. The se...

Geostatistical analyses require an estimation of the covariance structure of a random field and its parameters jointly from noisy data. Whereas in some cases (as in that of a Matérn variogram) a range of structural models can be captured with one or a few parameters, in many other cases it is necessary to consider a discrete set of structural model alternatives, such as drifts and variograms. R...