We review the normalized maximum likelihood (NML) criterion for selecting among competing models. NML is generally justified on information-theoretic grounds, via the principle of minimum description length (MDL), in a derivation that “does not assume the existence of a true, data-generating distribution.” Since this “agnostic” claim has been a source of some recent confusion in the psychologic...

This paper shows that the normalized maximum likelihood (NML) code-length calculated in [1] is an upper bound on the NML code-length strictly calculated for the Gaussian Mixture Model. We call an upper bound on the NML code-length as uNML (upper bound on NML). When we use this uNML code-length, we have to change the scale of data sequence to satisfy the restricted domain. However, in the point ...

The random moderation model (RMM) was developed based on a two-level regression to cope with heteroscedasticity in analysis, and normal-distributed-based maximum likelihood (NML) estimation estimate the RMM. To present an alternative NML, this article discusses effectiveness of Bayesian for RMM, aiming explore more practical method using popular software Mplus. Through simulation study, RMM inv...

We report new observations of the far infrared and submillimeter water vapor emission of NML Cygnus based on data gathered with the Infrared Space Observatory and the Submillimeter Wave Astronomy Satellite. We compare the emission from NML Cyg to that previously published for VY CMa and W Hya in an attempt to establish the validity of recently proposed models for the outflow from evolved stars....

The design of modern embedded systems require automated modeling tools for faster design and for the study of various design tradeo s. Such tools put together constitute an integrated environment where the designer can write the high level design speci cations in a language and use these tools for automatic generation of system speci c tools. In this work we have designed a Retargetable Functio...

This article presents a non-technical perspective on two prominent methods for analyzing experimental data in order to select among model classes. Each class consists of model instances; each instance predicts a unique distribution of data outcomes. One method is Bayesian Model Selection (BMS), instantiated with the Bayes factor. The other is based on the Minimum Description Length principle (M...

A novel spectrophotometric reaction system was developed for the determination of nitrite as well as nitrate in water samples, and was applied to a flow-injection analysis (FIA). The spectrophotometric flow-injection system coupled with a copperised cadmium reductor column was proposed. The detection was based on the nitrosation reaction between nitrite ion and phloroglucinol (1,3,5-trihydroxyb...

This report outlines the results of various experiments to model the probability of an area-frame farm not being on the census mailing list (NML) using covariates such as total sales, type of farm, acreage, various operator characteristics (gender, Hispanic status, race, and whether the primaryl occupation of the principal operator is farming), number (if any) of equine on the farm, and, option...

ABD (Anaerobic Biodegradability) and BMP (Biochemical Methane Potential) of banana plant waste, canola straw, cotton stalks, rice straw, sugarcane trash and wheat straw co-digested with buffalo dung was evaluated through AMPTS (Automatic Methane Potential Test System). The substrates were analyzed for moisture, TS (Total Solids) and VS (Volatile Solids), ultimate analysis (CHONS), pH and TA (To...

The stochastic complexity (SC) selects from a given family of parametric models the one that yields the shortest code length for the available measurements. Theoretical developments have made possible the evolution of the SC from the “two-part code” formula to the most recent expression based on the so-called Normalized Maximum Likelihood (NML) distribution. The application of the NML criterion...