• Journal of Energy Engineering
• /
• v.23 no.3
• /
• pp.36-41
• /
• 2014

The world's overall need for natural gas (NG) has been growing up fast, especially in the residential sector. The better the estimation of residential NG consumption (RNGC) distribution, the better decision-making for a residential NG policy such as pricing, demand estimation, management options and so on. Approximating the distribution of RNGC is complicated by zero observations in the sample. To deal with the zero observations by allowing a point mass at zero, a mixture model of RNGC distributions is proposed and applied. The RNGC distribution is specified as a mixture of two distributions, one with a point mass at zero and the other with full support on the positive half of the real line. The model is empirically verified for household RNGC survey data collected in Korea. The mixture model can easily capture the common bimodality feature of the RNGC distribution. In addition, when covariates were added to the model, it was found that the probability that a household has non-expenditure significantly varies with some variables. Finally, the goodness-of-fit test suggests that the data are well represented by the mixture model.

• Environmental and Resource Economics Review
• /
• v.12 no.3
• /
• pp.453-467
• /
• 2003

Approximating a WTP distribution of the conservation for Hallyue Marine National Park is complicated by zero observations in the sample. To deal with the zero observations, a mixture model is considered to allow a point mass at zero. The model is empirically verified for the data. The conventional model and a spike model are also considered for comparison. Our results portrays the usefulness of the mixture model to analyze SBDC data with zero observations.

• Environmental and Resource Economics Review
• /
• v.11 no.2
• /
• pp.321-333
• /
• 2002

Approximating bottled water consumption distribution is complicated by zero observations in the sample. To deal with the zero observations, a mixture model of bottled water consumption distributions is proposed and applied to allow a point mass at zero. The bottled water consumption distribution is specified as a mixture of two distributions, one with a point mass at zero and the other with full support on the positive half of the real line. The model is empirically verified for household bottled water consumption survey data. The mixture model can easily capture the common bimodality feature of the bottled water consumption distribution. In addition, when covariates were added to the model, it was found that the probability that a household has non-consumption significantly varies with some variables.

• Communications of Mathematical Education
• /
• v.5
• /
• pp.513-522
• /
• 1997

• The Korean Journal of Applied Statistics
• /
• v.25 no.5
• /
• pp.859-864
• /
• 2012

Poisson regression and negative binomial regression are usually used to analyze counting data; however, these models are unsuitable for fit zero-inflated data that contain unexpected zero-valued observations. In this paper, we review the zero-inflated regression in which Bernoulli process and the counting process are hierarchically mixed. It is known that zero-inflated regression can efficiently model the over-dispersion problem. Vuong statistic is employed to compare performances of the zero-inflated models with other standard models.

• The Bulletin of The Korean Astronomical Society
• /
• v.46 no.1
• /
• pp.48.1-48.1
• /
• 2021

Gaussian process regression (GPR) is a powerful method used for model-independent analysis of cosmological observations. In GPR, it is important to decide an input mean function and hyperparameters that affect the reconstruction results. Depending on how the input mean function and hyperparameters are determined in the literature, I divide into four main applications for GPR and compare their results. In particular, a zero mean function is commonly used as an input mean function, which may be inappropriate for reconstructing cosmological observations such as the distance modulus. Using mock data based on Pantheon compilation of type Ia supernovae, I will point out the problem of using a zero input and suggest a new way to deal with the input mean function.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.1 no.1
• /
• pp.147-150
• /
• 1976

Optimal stopping problem without recall from a multivariate distribution is solved by using the concept of an equilibrium point which was introduced by J. Nash. The solution is derived for the two cases: 1. The case where the observation cost C is positive and the given upper bound K on the number of observations is infinite. 2. The case where the observation cost C is zero and the given upper bound K on the number of observations is finite.

• Publications of The Korean Astronomical Society
• /
• v.11 no.1
• /
• pp.57-73
• /
• 1996

As a continuing effort to develop an automatic control system for small telescope, we developed the software for telescope control and CCD observations under DOS operating system. For accurate pointing of the telescope in short amount of time, we modelled the angular speed of the telescope by aquadratic function of time (constant acceleration) for the first 15 second and then linear function of time (zero acceleration) aftwewards. By changing the telescope speed from 'slew' to 'fine' before the telescope reaches the desired position, we could achieve the accuracy of a few arcsecond. The CCD control software was written for model CCD-10 of CCD Technology. This CCD can be used for guiding purposes. We also conducted the study for remote control of the telescope using telephone line. Although it cannot be used for real observations at the present form, we succeded in remotely pointing the telescope to desired direction. As faster communication technologies become widely available, simple observations can be made remotely in the near future. Finally we report some observational results made with the present control system.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.8C
• /
• pp.709-712
• /
• 2010

In this paper, the two sample locally optimum rank detector is obtained in the weakly dependent noise with non-zero temporal correlation between noise observations. The test statistic of the locally optimum rank detector is derived from the Neyman-Pearson lemma suitable for the two sample observation models, where it is assumed that reference observations are available in addition to regular observations. Two-sample locally optimum rank detecter shows the same performance with the one-sample locally optimum rank detector asymptotically. The structure of the two-sample rank detector is simpler than that of the one-sample rank detector because the sign statistic is not processed separately.

• The Korean Journal of Applied Statistics
• /
• v.24 no.3
• /
• pp.485-494
• /
• 2011

When the observations can take only the non-negative integer values, it is called the count data such as the numbers of car accidents, earthquakes, or insurance coverage. In general, the Poisson regression model has been used to model these count data; however, this model has a weakness in that it is restricted by the equality of the mean and the variance. On the other hand, the count data often tend to be too dispersed to allow the use of the Poisson model in practice because the variance of data is significantly larger than its mean due to heterogeneity within groups. When overdispersion is not taken into account, it is expected that the resulting parameter estimates or standard errors will be inefficient. Since coverage is the main issue for insurance, some accidents may not be covered by insurance, and the number covered by insurance may be zero. This paper considers the zero-inflated model for the count data including many zeros. The performance of this model has been investigated by using of real data with overdispersion and many zeros. The results indicate that the Zero-Inflated Negative Binomial Regression Model performs the best for model evaluation.