• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.963-972
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• 2006

This paper focuses on the likelihood based confidence intervals for two inverse gaussian distributions when the parameter of interest is common scale parameter. Confidence intervals based on signed loglikelihood ratio statistic and modified signed loglikelihood ratio statistics will be compared in small sample through an illustrative simulation study.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.177-182
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• 2022

Technology is progressing with every passing day and the enormous usage of electricity is becoming a necessity. One of the techniques to enjoy the assistances in a smart home is the efficiency to manage the electric energy. When electric energy is managed in an appropriate way, it drastically saves sufficient power even to be spent during hard time as when hit by natural calamities. To accomplish this, prediction of energy consumption plays a very important role. This proposed prediction model Coherent Weighted K-Means Clustering ARIMA (CWKMCA) enhances the weighted k-means clustering technique by adding weights to the cluster points. Forecasting is done using the ARIMA model based on the centroid of the clusters produced. The dataset for this proposed work is taken from the Pecan Project in Texas, USA. The level of accuracy of this model is compared with the traditional ARIMA model and the Weighted K-Means Clustering ARIMA Model. When predicting,errors such as RMSE, MAPE, AIC and AICC are analysed, the results of this suggested work reveal lower values than the ARIMA and Weighted K-Means Clustering ARIMA models. This model also has a greater loglikelihood, demonstrating that this model outperforms the ARIMA model for time series forecasting.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.296-302
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• 1995

When heteroscedasticity occurs in random effects linear model, the error variance may depend on the values of one or more of the explanatory variables or on other relevant quantities such as time or spatial ordering. In this paper we derive a score test as a diagnostic tool for detecting non-constant error variance in random effefts linear model based on the model expansion on error variance. This score test is compared to loglikelihood ratio test.

• Health Policy and Management
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• v.5 no.2
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• pp.155-172
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• 1995

This study is an empirical analysis on the equity in the delivery of heatlh care under the Korean Medical Insurance Corporation System. The purposes of this study are to find out effects of income on the health care utiliztion and measure the income-related inequity in the distribution of health care. This study was carried out based on the fact that the health insurance program has been organized to achieve the equity objective, "equal treatment for equal needs". Of 41, 828 insured persons who had been diagnosed in the 1993 Health Screening Test and utilifzation data from 1, January 1993 through 31, December 1993 were derived from the Benefit Managment File. Inequity was measured by means of I) share approach, ii) standardization concentration curve approach, iii) inequity index, iv) test for inequity. The major findings were as follows : 1. The expenditure shares of the top two quintile groups exceeded their morbidity shares, whereas the opposite was true of the bottom three quintile groups, Which showed a positive HI$_{LG}$ inequity index, suggesting the presence of some inequity favoring the rich group. 2. Compared with other residential areas, the rural area showed the highest positive HI$_{LG}$ irrespective of need indicatior applied. 3. Standardized expenditure concentration indices adjusted by age, gender and need structure were also found to be positive, and therefore still indicated that there has been inequity favoring the rich after the standardization. 4. The Loglikelihood Ratio (LR) test for the statistical significance of income-related inequity of medical care utilization was carried out using the logistic regression model. The resulting loglikelihood ratio test statistic value was 176, which did exceed the 0.5 percent critical value of the chi-square distribution with 28 degrees of freedom, which is 50.993. Therefore, the null hypothesis of no income-related inequity of medical care utilization was rejected at the 99.5 percent confidence level. 5. The Regression based F-test has been carried out for analyzing the income-related inequity of medical expenditure in terms of age, gender, morbidity indicators as explanary variables. The hypothesis of the absence of income-relate inequity was rejected for all need indicators at the 95% confidence level.nce level.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.919-925
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• 2006

Maximum likelihood estimate(MLE) is obtained from the partial log-likelihood function for the cell probabilities of two way incomplete contingency tables proposed by Chen and Fienberg(1974). The partial log-likelihood function is modified by adding lagrangian multiplier that constraints can be incorporated with. Variances of MLE estimators of population proportions are derived from the matrix of second derivatives of the loglikelihood with respect to cell probabilities. Simulation results, when data are missing at random, reveal that Complete-case(CC) analysis produces biased estimates of joint probabilities under MAR and less efficient than either MLE or MI. MLE and MI provides consistent results under either the MAR situation. MLE provides more efficient estimates of population proportions than either multiple imputation(MI) based on data augmentation or complete case analysis. The standard errors of MLE from the proposed method using lagrangian multiplier are valid and have less variation than the standard errors from MI and CC.

• Journal of Forest and Environmental Science
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• v.34 no.6
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• pp.451-456
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• 2018

The use of single component distribution to describe the irregular stand structure of degraded forest often lead to bias. Such biasness can be overcome by the application of finite mixture distribution. Therefore, in this study, finite mixture distribution was used to characterise the irregular stand structure of the Gmelina arborea plantation in Omo forest reserve. Thirty plots, ten each from the three stands established in 1984, 1990 and 2005 were used. The data were pooled per stand and fitted. Four finite mixture distributions including normal mixture, lognormal mixture, gamma mixture and Weibull mixture were considered. The method of maximum likelihood was used to fit the finite mixture distributions to the data. Model assessment was based on negative loglikelihood value ($-{\Lambda}{\Lambda}$), Akaike information criterion (AIC), Bayesian information criterion (BIC) and root mean square error (RMSE). The results showed that the mixture distributions provide accurate and precise characterisation of the irregular diameter distribution of the degraded Gmelina arborea stands. The $-{\Lambda}{\Lambda}$, AIC, BIC and RMSE values ranged from -715.233 to -348.375, 703.926 to 1433.588, 718.598 to 1451.334 and 3.003 to 7.492, respectively. Their performances were relatively the same. This approach can be used to describe other irregular forest stand structures, especially the multi-species forest.