• Environmental and Resource Economics Review
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• v.13 no.4
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• pp.717-734
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• 2004

This paper examined the statistical goodness-of-fit tests for biological growth model in bioeconomic analysis. Some authors estimated usually growth function for fish in the world. However, few studies have estimated growth equations for the bivalve species. Thus, this paper studied the common functional forms of fitting growth equations for cham scallops considering environmental factors and production styles. The following functional forms are considered: linear, log-reciprocal, double log, polynomial and linear with interactions. Results of fitting these various functional forms with real data are compared and evaluated using standard statistical goodness-of-fit tests. Results also indicate that log-reciprocal function is statistically the best fit to the real data. Therefore, the log-reciprocal function is decided the best function describing cham scallop biological growth and hence might be useful for economic evaluation(i.e., optimal harvesting time).

• Journal of Soil and Groundwater Environment
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• v.27 no.6
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• pp.47-57
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• 2022

A number of different methods have been used for modeling the sorption of volatile organic chlorinated compounds such as tetrachloroethylene/perchloroethylene (PCE). In this study, PCE was adsorbed in several natural sorbents, i.e., Pahokee peat, vermicompost, BionSoil^®, and natural soil, in the batch experiments. Several sorption models such as linear, Freundlich, solubility-normalized Freundlich model, and Polanyi-Manes model (PMM) were used to analyze sorption isotherms. The relationship between sorption model parameters, organic carbon content (f_oc), and elemental C/N ratio was studied. The organic carbon normalized partition coefficient values (log K_oc = 1.50-3.13) in four different sorbents were less than the logarithm of the octanol-water partition coefficient (log K_ow = 3.40) of PCE due to high organic carbon contents. The log K_oc decreased linearly with log f_oc and log C/N ratio, but increased linearly with log O/C, log H/C, and log (N+O)/C ratio. Both log K_F,oc or log K_F,oc decreased linearly with log f_oc (R² = 0.88-0.92) and log C/N ratio (R² = 0.57-0.76), but increased linearly with log (N+O)/C (R² = 0.93-0.95). The log q_max,oc decreased linearly as log f_oc and log C/N increased, whereas it increased with log O/C, log H/C and log (N+O)/C ratios. The log q_max,oc increased linearly with (N+O)/C indicating a strong dependence of q_max,oc on the polarity index. The results showed that PCE sorption behaviors were strongly correlated with the physicochemical properties of soil organic matter (SOM).

• Communications for Statistical Applications and Methods
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• v.5 no.3
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• pp.847-853
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• 1998

Suppose we want to compare following non-hierarchical log-linear models, $H_0:f(x, heta inTheta_a)$ vs H_1:g(x, heta inTheta_eta); for; Theta_a,;Theta_etasubsetTheta;such;that;Theta_$\alpha$/ Theta_eta$. The goodness of fit test using the likelihood ratio test statistic for comparing these models could not be acceptable. By using the polyhedrons plots of Choi and Hong (1995), we propose a method to decide a better model between two non-hierarchical log-linear models $f(x: heta inTheta_a) and g(x: heta inTheta_eta)$.

• Communications for Statistical Applications and Methods
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• v.13 no.2
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• pp.297-307
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• 2006

Most methods for describing the relationship among random variables require specific probability distributions and some assumptions of random variables. The mutual information based on the entropy to measure the dependency among random variables does not need any specific assumptions. And the redundancy which is a analogous version of the mutual information was also proposed. In this paper, the redundancy and mutual information are explored to multi-dimensional categorical data. It is found that the redundancy for categorical data could be expressed as the function of the generalized likelihood ratio statistic under several kinds of independent log-linear models, so that the redundancy could also be used to analyze contingency tables. Whereas the generalized likelihood ratio statistic to test the goodness-of-fit of the log-linear models is sensitive to the sample size, the redundancy for categorical data does not depend on sample size but its cell probabilities itself.

• Communications for Statistical Applications and Methods
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• v.14 no.2
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• pp.401-411
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• 2007

In this paper we propose an influence measure for detecting potentially influential observations using the infinitesimal perturbation and the local influence in the log-linear regression model. Also, we propose a goodness-of-fit measure for variable selection. A real data set are used for illustration.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.310-319
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• 1995

We represent graphically the relationship of hierachical log linear models by regarding the values of the likelihood ratio statistics as the squared norm of the corresponding vectors. Right angled triangles, tetrahedrons, and modified polyhedrons are used for graphical description. We find that the angle between the two vectors depends on the coefficient of determination and the partial coefficent of determination. Thess graphical descriptions could be applied to the model selection method.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.775-791
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• 2017

We frequently encounter binary data in real life. Logistic, Probit, Cauchit, Complementary log-log models are often used for binary data analysis. In order to analyze binary data, Liu (2004) proposed a Robit model, in which the inverse of cdf of the Student's t distribution is used as a link function. Kim et al. (2008) also proposed a generalized t-link model to make the binary regression model more flexible. The more flexible skewed distributions allow more flexible link functions in generalized linear models. In the sense, we propose a binary data regression model using skewed generalized t distributions introduced in Theodossiou (1998). We implement R code of the proposed models using the glm function included in R base and R sgt package. We also analyze Pima Indian data using the proposed model in R.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.135-144
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• 2003

This work is concerned with comparison of the recently developed disparity measures for the partial association model in three dimensional categorical data. Data are generated by using simulation on each term in the log-linear model equation based on the partial association model, which is a proposed method in this paper. This alternative Monte Carlo methods are explored to study the behavior of disparity measures such as the power divergence statistic I(λ), the Pearson chi-square statistic X$^2$, the likelihood ratio statistic G$^2$, the blended weight chi-square statistic BWCS(λ), the blended weight Hellinger distance statistic BWHD(λ), and the negative exponential disparity statistic NED(λ) for moderate sample sizes. We find that the power divergence statistic I(2/3) and the blended weight Hellinger distance family BWHD(1/9) are the best tests with respect to size and power.

• Journal of Internet Computing and Services
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• v.20 no.3
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• pp.85-92
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• 2019

In this paper, we extract the quantitative relation data of activities from the workflow event log file recorded in the XES standard format and connect them to rediscover the workflow process model. Extract the workflow process patterns and proportions with the rediscovered model. There are four types of control-flow elements that should be used to extract workflow process patterns and portions with log files: linear (sequential) routing, disjunctive (selective) routing, conjunctive (parallel) routing, and iterative routing patterns. In this paper, we focus on four of the factors, disjunctive routing, and conjunctive path. A framework implemented by the authors' research group extracts and arranges the activity data from the log and converts the iteration of duplicate relationships into a quantitative value. Also, for accurate analysis, a parallel process is recorded in the log file based on execution time, and algorithms for finding and eliminating information distortion are designed and implemented. With these refined data, we rediscover the workflow process model following the relationship between the activities. This series of experiments are conducted using the Large Bank Transaction Process Model provided by 4TU and visualizes the experiment process and results.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.9
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• pp.5367-5370
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• 2013

Background: Having knowledge or estimation of cancer incidence is necessary for planning and implementation of any cancer prevention and control programs. Population-based registries provide valuable information to achieve these objectives but require extra techniques to estimate the incidence rate. The present study aimed to estimate the esophageal cancer incidence using a log-linear method based on Tehran population-based cancer registry data. Materials and Methods: New cases of esophageal cancer reported by three sources of pathology reports, medical records, and death certificates to Tehran Metropolitan Area Cancer Registry Center during 2002-2006 were entered into the study and the incidence rate was estimated based on log-linear models. We used Akaike statistics to select the best-fit model. Results: During 2002-2006, 1,458 new cases of esophageal cancer were reported by the mentioned sources to the population-based cancer registry. Based on the reported cases, cancer incidence was 4.5 per 100,000 population and this was estimated to be 10.5 per 100,000 by the log-linear method. Conclusions: Based on the obtained results, it can be concluded that an estimated incidence for 2004 of 8.3 per 100,000 population could be a good benchmark for the incidence of esophageal cancer in the population of Tehran metropolis.