• Title/Summary/Keyword: Term Statistics

Search Result 752, Processing Time 0.027 seconds

Comparison of a Class of Nonlinear Time Series models (GARCH, IGARCH, EGARCH) (이분산성 시계열 모형(GARCH, IGARCH, EGARCH)들의 성능 비교)

  • Kim S.Y.;Lee Y.H.
    • The Korean Journal of Applied Statistics
    • /
    • v.19 no.1
    • /
    • pp.33-41
    • /
    • 2006
  • In this paper, we analyse the volatilities in financial data such as stock prices and exchange rates in term of a class of nonlinear time series models. We compare the performance of Generalized Autoregressive Conditional Heteroscadastic(GARCH) , Integrated GARCH(IGARCH), Exponential GARCH(EGARCH) models by KOSPI (Korean stock Prices Index) data. The estimation for the parameters in the models was carried out by the ML methods.

Ruin Probability on Insurance Risk Models (보험위험 확률모형에서의 파산확률)

  • Park, Hyun-Suk;Choi, Jeong-Kyu
    • The Korean Journal of Applied Statistics
    • /
    • v.24 no.4
    • /
    • pp.575-586
    • /
    • 2011
  • In this paper, we study an asymptotic behavior of the finite-time ruin probability of the compound Poisson model in the case that the initial surplus is large. To compare an exact ruin probability with an approximate one, we place the focus on the exact calculation for the ruin probability when the claim size distribution is regularly varying tailed (i.e. exponential claims and inverse Gaussian claims). We estimate an adjustment coefficient in these examples and show the relationship between the adjustment coefficient and the safety premium. The illustration study shows that as the safety premium increases so does the adjustment coefficient. Larger safety premium means lower "long-term risk", which only stands to reason since higher safety premium means a faster rate of safety premium income to offset claims.

A Statistical Analysis on Temperature Change and Climate Variability in Korea (한국의 기온변화와 기온변동성에 대한 통계적 연구)

  • Kim, Hyun-Chul;Choi, Seung-Kyung;Yun, Bo-Ra
    • Communications for Statistical Applications and Methods
    • /
    • v.18 no.1
    • /
    • pp.1-12
    • /
    • 2011
  • We analyzed the observed temperature data for 50 years on 5 representative points in Korea to verify global warming and the increase in climate variability. We found that there was some level of global warming but we could not disregard the effects of urbanization. In addition, we could not find any information for the increase in climate variability.

A Discrete Feature Vector for Endpoint Detection of Speech with Hidden Markov Model (숨은마코프모형을 이용하는 음성 끝점 검출을 위한 이산 특징벡터)

  • Lee, Jei-Ky;Oh, Chang-Hyuck
    • The Korean Journal of Applied Statistics
    • /
    • v.21 no.6
    • /
    • pp.959-967
    • /
    • 2008
  • The purpose of this paper is to suggest a discrete feature vector, robust in various levels of noisy environment and inexpensive in computation, for detection of speech segments and is to show such properties of the feature with real speech data. The suggested feature is one dimensional vector which represents slope of short term energies and is discretized into three values to reduce computational burden of computations in HMM. In experiments with speech data, the method with the suggested feature vector showed good performance even in noisy environments.

Estimating the Transmittable Prevalence of Infectious Diseases Using a Back-Calculation Approach

  • Lee, Youngsaeng;Jang, Hyun Gap;Kim, Tae Yoon;Park, Jeong-Soo
    • Communications for Statistical Applications and Methods
    • /
    • v.21 no.6
    • /
    • pp.487-500
    • /
    • 2014
  • A new method to calculate the transmittable prevalence of an epidemic disease is proposed based on a back-calculation formula. We calculated the probabilities of reactivation and of parasitemia as well as transmittable prevalence (the number of persons with parasitemia in the incubation period) of malaria in South Korea using incidence of 12 years(2001-2012). For this computation, a new probability function of transmittable condition is obtained. The probability of reactivation is estimated by the least squares method for the back-calculated longterm incubation period. The probability of parasitemia is calculated by a convolution of the survival function of the short-term incubation function and the probability of reactivation. Transmittable prevalence is computed by a convolution of the infected numbers and the probabilities of transmission. Confidence intervals are calculated using the parametric bootstrap method. The method proposed is applicable to other epidemic diseases in other countries where incidence and a long incubation period are available. We found the estimated transmittable prevalence in South Korea was concentrated in the summer with 276 cases on a peak at the $31^{st}$ week and with about a 60% reduction in the peak from the naive prevalence. The statistics of transmittable prevalence can be used for malaria prevention programs and to select blood transfusion donors.

A study on parsimonious periodic autoregressive model (모수 절약 주기적 자기회귀 모형에 관한 연구)

  • Lee, Jiho;Seong, Byeongchan
    • The Korean Journal of Applied Statistics
    • /
    • v.29 no.1
    • /
    • pp.133-144
    • /
    • 2016
  • This paper proposes a parsimonious periodic autoregressive (PAR) model. The proposed model performance is evaluated through an analysis of Korean unemployment rate series that is compared with existing models. We exploit some common features among each seasonality and confirm it by LR test for the parsimonious PAR model in order to impose a parsimonious structure on the PAR model. We observe that the PAR model tends to be superior to existing seasonal time series models in mid- and long-term forecasts. The proposed parsimonious model significantly improves forecasting performance.

A Study on the Short Term Internet Traffic Forecasting Models on Long-Memory and Heteroscedasticity (장기기억 특성과 이분산성을 고려한 인터넷 트래픽 예측을 위한 시계열 모형 연구)

  • Sohn, H.G.;Kim, S.
    • The Korean Journal of Applied Statistics
    • /
    • v.26 no.6
    • /
    • pp.1053-1061
    • /
    • 2013
  • In this paper, we propose the time series forecasting models for internet traffic with long memory and heteroscedasticity. To control and forecast traffic volume, we first introduce the traffic forecasting models which are determined by the volatility and heteroscedasticity of the traffic. We then analyze and predict the heteroscedasticity and the long memory properties for forecasting traffic volume. Depending on the characteristics of the traffic, Fractional ARIMA model, Fractional ARIMA-GARCH model are applied and compared with the MAPE(Mean Absolute Percentage Error) Criterion.

Review on LTE-Advanced Mobile Technology

  • Seo, Dae-woong;Kim, Yoon-Hwan;Song, Jeong-Sang;Jang, Bongseog;Bae, Sang-Hyun
    • Journal of Integrative Natural Science
    • /
    • v.11 no.4
    • /
    • pp.197-203
    • /
    • 2018
  • Long Term Evolution-Advanced (LTE-A) is the next drive in the broadband mobile communication, which allows operators to improve networks performance and service capabilities. LTE-A targets the peak data rates of 1Gbps in the downlink and 500Mbps in the uplink. This requirement is only fulfilled by a transmission bandwidth of up to 100MHz. However the accessibility of such large part of the contiguous spectrum is uncommon in practice. Therefore LTE-A uses some new features on top of the existing LTE standards to provide very high data rate transmission. Some of the most significant features introduced in LTE-A are carrier aggregation, heterogeneous network enhancement, coordinated multipoint transmission and reception, enhanced multiple input and multiple output, and development relay nodes with universal frequency reuse. This review paper presents an overview of the above mentioned LTE-A key features and functionalities. Based on this review, in the conclusion we discuss the current technical challenges for future broadband mobile communication systems.

Analysis of speech in game marketing video using text mining techniques (텍스트 마이닝 기법을 이용한 게임 마케팅 비디오에서의 스피치 분석)

  • Lee, Yeokyung;Kim, Jaejik
    • The Korean Journal of Applied Statistics
    • /
    • v.35 no.1
    • /
    • pp.147-159
    • /
    • 2022
  • Nowadays, various social media platforms are widely spread and people closely use such platforms in daily life. By doing so, social influencers with a large number of subscribers, views, and comments have huge impact in our society. Following this trend, many companies are actively using influencers for marketing purpose to promote their products and services. In this study, we extract the speeches of influencers from videos for game marketing and analyze them using various text mining techniques. In the analysis, we distinguish game videos leading to successful marketing and failed marketing, and we explore and compare the linguistic features of the influencers for successful and failed marketings.

Comparison of TERGM and SAOM : Statistical analysis of student network data (TERGM과 SAOM 비교 : 학생 네트워크 데이터의 통계적 분석)

  • Yujin Han;Jaehee Kim
    • The Korean Journal of Applied Statistics
    • /
    • v.36 no.1
    • /
    • pp.1-19
    • /
    • 2023
  • The purpose of this study was to find out what attributes are valid for the edge between students through longitudinal network analysis, and the results of TERGM (temporal exponential random graph model) and SAOM (stochastic actor-oriented model) statistical models were compared. The TERGM model interprets the research results based on the edge formation of the entire network, and the SAOM model interprets the research results on the surrounding networks formed by specific actors. The TERGM model expressed the influence of a previous time through a time term, and the SAOM model considered temporal dependence by implementing a network that evolves by an actor's opportunity as a ratio function.