Journal of Data Science

Abstract: A field study was carried out to determine the spatial distribution of air dose rate on grazed grassland after the earthquake on 11 March, 2011 in the Northwest Pacific of Northeastern Japan. Data on air dose rates (µSv h-1) were collected from Ichinoseki, south of Iwate Prefecture, Japan. Air dose rates were collected from each of 1 m interval of 12 ×12 m2 site (L-site). At the center of Lsite, 1.2 ×1.2 m2 site (S-site) was located. One hundred and forty four (144) equal spaced quadrats were defined in the S-site. Again, air dose rates were collected from central point of each of the quadrat. Moran’s I, a measure of autocorrelation was used to test the spatial heterogeneity of air dose rate on grazed grassland. Autocorrelation in S-site area was significantly higher than L-site area. Air dose rate did not show significant autocorrelation at any spatial lag in L-site. In S-site, air dose rate level showed significant autocorrelation in twelve of sixteen spatial lag. Autocorrelograms and Moran’s scatterplot showed that air dose rate was frequently and positively spatially correlated at distance less than 0.1 m.

In reliability and life-testing experiments, the researcher is often interested in the effects of extreme or varying stress factors on the lifetimes of experimental units. In this paper, a step-stress model is considered in which the life-testing experiment gets terminated either at a pre-fixed time (say, Tm+1) or at a random time ensuring at least a specified number of failures (Say, y out of n). Under this model in which the data obtained are Type-II hybrid censored, the Kumaraswamy Weibull distribution is used for the underlying lifetimes. The maximum Likelihood estimators (MLEs) of the parameters assuming a cumulative exposure model are derived. The confidence intervals of the parameters are also obtained. The hazard rate and reliability functions are estimated at usual conditions of stress. Monte Carlo simulation is carried out to investigate the precision of the maximum likelihood estimates. An application using real data is used to indicate the properties of the maximum likelihood estimators.

Most research on housing price modeling utilize linear regression models. These research mostly describe the actual contribution of factors in a linear way on magnitude, including positive or negative. The goal of this paper is to identify the non-linear patterns for 3 major types of real estates through model building that includes 49 housing factors. The datasets were composed by 33,027 transactions in Taipei City from July 2013 to the end of 2016. The non-linear patterns present in the combination manner of a sequence of uptrends and downtrends that are derived from Generalized Additive Models (GAM).

Abstract: Consider the problem of selecting independent samples from several populations for the purpose of between-group comparisons. An important aspect of the solution is the determination of clusters where mean levels are equal, often accomplished using multiple comparisons testing. We formulate the hypothesis testing problem of determining equal-mean clusters as a model selection problem. Information from all competing models is combined through Bayesian methods in an effort to provide a more realistic accounting of uncertainty. An example illustrates how the Bayesian approach leads to a logically sound presentation of multiple comparison results.

Families of distributions are commonly used to model insurance claims data that require flexible distributional forms in a satisfactory manner, but the specification problem to assess the goodness-of-fit of the hypothesized model can sometimes be a challenge due to the complexity of the likelihood function of the family of distributions involved. The previous work shows that these specification problems can be attacked by means of semi-parametric tests based on generalized method of moment (GMM) estimators. While the approach can be directly applied to both discrete and continuous families of distributions, the paper focuses on developing a testing strategy within a framework of discrete families of distributions. Both the local power analysis and the approximate slope method demonstrate the excellent performance of these tests. The finite-sample performance of the tests, based on both asymptotic and bootstrap critical values, are also discussed and are compared with established methods that require the complete specification of likelihood functions.

Abstract: Controlled experiments give researchers a statistical tool for determining the yield from subjecting an experimental unit to various treat ments. We will discuss a replicated, block design applied to the experimental unit yeast. We subjected the yeast to six treatments. The purpose of the experiment is to extract a compound to be used in the manufacturing in dustry. We considered an ANOVA and a MANOVA model to analyze the data. The rationale for selecting one model over the other will be discussed. Results and recommendations of which treatments to use when processing the yeast will be presented, also.

Abstract: In this paper, we obtain several estimators of a scale parameter of Morgenstern type bivariate uniform distribution (MTBUD) based on the observations made on the units of the ranked set sampling regarding the study variable Y which is correlated with the auxiliary variable X, when (X, Y ) follows a MTBUD. Efficiency comparisons among these estimators are also made in this work. Finally, we illustrate the methods developed by using a real data set.