• Title/Summary/Keyword: short-rate models

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A Semi-empirical Mass-loss Rate in Short-period CVs

  • Kim, Woong-Tae;Sirotkin, Fedir V.
    • The Bulletin of The Korean Astronomical Society
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    • v.35 no.2
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    • pp.76.2-76.2
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    • 2010
  • We present the final results of our study on the mass-loss rate of donor stars in cataclysmic variables (CVs). Observed donors are oversized in comparison with those of isolated single stars of the same mass, which is thought to be a consequence of the mass loss. Using the empirical mass-radius relation of CVs and the homologous approximation for changes in effective temperature T2, orbital period P, and luminosity of the donor with the stellar radius, we find the semi-empirical mass-loss rate M2dot of CVs as a function of P. The derived M2dot is at ~10-9.5-10-10 $M\odot$/yr and depends weakly on P when P > 90 min, while it declines very rapidly towards the minimum period when P < 90 min. The semi-empirical M2dot is significantly different from, and has a less-pronounced turnaround behavior with P than suggested by previous numerical models. The semi-empirical P-M2dot relation is consistent with the angular momentum loss due to gravitational wave emission, and strongly suggests that CV secondaries with 0.075 $M\odot$ < M2 < 0.2 $M\odot$ are less than 2 Gyrs old. When applied to selected eclipsing CVs, our semi-empirical mass-loss rates are in good agreement with the accretion rates derived from the effective temperatures T1 of white dwarfs. Based on the semi-empirical M2dot, SDSS 1501 and 1433 systems that were previously identified as post-bounce CVs have yet to reach the minimal period.

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Impulse Response of Inflation to Economic Growth Dynamics: VAR Model Analysis

  • DINH, Doan Van
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.9
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    • pp.219-228
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    • 2020
  • The study investigates the impact of inflation rate on economic growth to find the best-fit model for economic growth in Vietnam. The study applied Vector Autoregressive (VAR), cointegration models, and unit root test for the time-series data from 1996 to 2018 to test the inflation impact on the economic growth in the short and long term. The study showed that the two variables are stationary at lag first difference I(1) with 1%, 5% and 10%; trace test indicates two cointegrating equations at the 0.05 level, the INF does not granger cause GDP, the optimal lag I(1) and the variables are closely related as R2 is 72%. It finds that the VAR model's results are the basis to perform economic growth; besides, the inflation rate is positively related to economic growth. The results support the monetary policy. This study identifies issues for Government to consider: have a comprehensive solution among macroeconomic policies, monetary policy, fiscal policy and other policies to control and maintain the inflation and stimulate growth; set a priority goal for sustainable economic growth; not pursue economic growth by maintaining the inflation rate in the long term, but take appropriate measures to stabilize the inflation at the best-fitted VAR forecast model.

A within-subject comparison of short implants in the posterior region: retrospective study of up to 10 years

  • Segalla, Douglas Blum;Villarinho, Eduardo Aydos;Correia, Andre Ricardo Maia;Vigo, Alvaro;Shinkai, Rosemary Sadami Arai
    • The Journal of Advanced Prosthodontics
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    • v.13 no.3
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    • pp.172-179
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    • 2021
  • Purpose. This intra-patient retrospective study of up to 10 years evaluated the clinical success and risk factors of 6- and 8-mm long implants and their respective prostheses. Materials and Methods. The sample consisted of patients treated at a Military Polyclinic dental service, who received both 6- and 8-mm long tissue level implants in the posterior region of the same arch. Data were collected from the dental charts, clinical and radiographic exams, self-report of sleep bruxism, measurement of maximum occlusal force, and clinical crown-to-implant (C/I) ratio. Data were analyzed by descriptive and inferential statistics with univariate and hierarchical multivariate models, at the 0.05 significance level. Results. The 30 patients (27 women) had 85 implants and 83 prostheses. Two implants were lost before prosthesis installation (implant survival: 97.6%). Ten events of prosthetic complication (screw tightening loss) occurred in five patients (success rate: 87.9%) in a single moment. Only the variable C/I ratio had a significant effect for repairable prosthesis complication (P<.05). Conclusion. The results suggest that 6- and 8-mm long implants have similar long-term clinical success for implants and prostheses.

Building of Prediction Model of Wind Power Generationusing Power Ramp Rate (Power Ramp Rate를 이용한 풍력 발전량 예측모델 구축)

  • Hwang, Mi-Yeong;Kim, Sung-Ho;Yun, Un-Il;Kim, Kwang-Deuk;Ryu, Keun-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.1
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    • pp.211-218
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    • 2012
  • Fossil fuel is used all over the world and it produces greenhouse gases due to fossil fuel use. Therefore, it cause global warming and is serious environmental pollution. In order to decrease the environmental pollution, we should use renewable energy which is clean energy. Among several renewable energy, wind energy is the most promising one. Wind power generation is does not produce environmental pollution and could not be exhausted. However, due to wind power generation has irregular power output, it is important to predict generated electrical energy accurately for smoothing wind energy supply. There, we consider use ramp characteristic to forecast accurate wind power output. The ramp increase and decrease rapidly wind power generation during in a short time. Therefore, it can cause problem of unbalanced power supply and demand and get damaged wind turbine. In this paper, we make prediction models using power ramp rate as well as wind speed and wind direction to increase prediction accuracy. Prediction model construction algorithm used multilayer neural network. We built four prediction models with PRR, wind speed, and wind direction and then evaluated performance of prediction models. The predicted values, which is prediction model with all of attribute, is nearly to the observed values. Therefore, if we use PRR attribute, we can increase prediction accuracy of wind power generation.

Forecasting Korean CPI Inflation (우리나라 소비자물가상승률 예측)

  • Kang, Kyu Ho;Kim, Jungsung;Shin, Serim
    • Economic Analysis
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    • v.27 no.4
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    • pp.1-42
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    • 2021
  • The outlook for Korea's consumer price inflation rate has a profound impact not only on the Bank of Korea's operation of the inflation target system but also on the overall economy, including the bond market and private consumption and investment. This study presents the prediction results of consumer price inflation in Korea for the next three years. To this end, first, model selection is performed based on the out-of-sample predictive power of autoregressive distributed lag (ADL) models, AR models, small-scale vector autoregressive (VAR) models, and large-scale VAR models. Since there are many potential predictors of inflation, a Bayesian variable selection technique was introduced for 12 macro variables, and a precise tuning process was performed to improve predictive power. In the case of the VAR model, the Minnesota prior distribution was applied to solve the dimensional curse problem. Looking at the results of long-term and short-term out-of-sample predictions for the last five years, the ADL model was generally superior to other competing models in both point and distribution prediction. As a result of forecasting through the combination of predictions from the above models, the inflation rate is expected to maintain the current level of around 2% until the second half of 2022, and is expected to drop to around 1% from the first half of 2023.

Analysis on Recent Changes in the Covered Interest Rate Parity Condition (글로벌 금융위기 전후 무위험 이자율 평형조건의 동태성 변화 분석)

  • Kim, Jung Sung;Kang, Kyu Ho
    • KDI Journal of Economic Policy
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    • v.36 no.2
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    • pp.103-136
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    • 2014
  • The covered interest rate parity condition (CIRP) has been widely used in open macroeconomic analysis, risk management, exchange rate forecasts, and so forth. Due to the recent global financial crises, there have been remarkable changes in the financial markets of the emerging markets. These changes possibly influenced the dynamics of the covered interest rate parity condition. In this paper, we investigate whether the CIRP dynamics has changed, and what is the nature of the regime changes. To do this, we propose and estimate multiple-state Markov regime switching models using a Bayesian MCMC method. Our estimation results indicate that the default risk or the deviation from the CIRP has been decreased after the crisis. It seems to be associated with the more active interaction between the short-term bond market and the short-term foreign exchange market than before. The tightened relation of these two financial markets is caused by the arbitrage transaction of foreign investors.

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UK Social Housing and Housing Market in England: A Statistical Review and Trends

  • Schmickler, Arno;Park, Kenneth Sungho
    • Land and Housing Review
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    • v.5 no.3
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    • pp.193-201
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    • 2014
  • Around 80% of the 63 million people in the UK live in urban areas where demand for affordable housing is highest. Supply of new dwellings is a long way short of demand and with an average annual replacement rate of 0.5% more than 80% of the existing residential housing stock will still be in use by 2050. A high proportion of owner-occupiers, a weak private rental sector and lack of sustainable financing models render England's housing market one of the least responsive in the developed world. As an exploratory research the purpose of this paper is to examine the provision of social housing in the United Kingdom with a particular focus on England, and to set out implications for housing associations delivering sustainable community development. The paper is based on an analysis of historical data series (Census data), current macro-economic data and population projections to 2033. The paper identifies a chronic undersupply of affordable housing in England which is likely to be exacerbated by demographic development, changes in household composition and reduced availability of finance to develop new homes. Based on the housing market trends analysed in this paper opportunities are identified for policy makers to remove barriers to the delivery of new affordable homes and for social housing providers to evolve their business models by taking a wider role in sustainable community development.

Low Temperature Thin Layer Drying Model of Rough Rice (벼의 저온 박층건조모델)

  • Kim H.;Keum D. H.;Kim O. W.
    • Journal of Biosystems Engineering
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    • v.29 no.6 s.107
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    • pp.495-500
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    • 2004
  • This study was performed to develop thin layer drying equations for low temperature. Thin layer drying tests of short grain rough rice were conducted at three low temperature levels of 15, 25, $35^{\circ}C$ and two relative humidity levels of 30, $50\%$, respectively. The measured moisture ratios were fitted to the selected four drying models (Page, Thompson, Simplified diffusion and Lewis model) using stepwise multiple regression analysis. The overall drying rate increased as the drying air temperature was increased and as relative humidity was decreased, but the effect of temperature increase was dominant. Half response time (Moisture ratio=0.5) of drying was affected by both drying temperature and relative humidity at drying temperature of below $25^{\circ}C$, but at $35^{\circ}C$ was mainly affected by drying temperature. The results of comparing coefficients of determination and root mean square error of moisture ratio for low drying models showed that Page model was found to fit adequately to all drying test data.

Analysis of quantitative high throughput screening data using a robust method for nonlinear mixed effects models

  • Park, Chorong;Lee, Jongga;Lim, Changwon
    • Communications for Statistical Applications and Methods
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    • v.27 no.6
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    • pp.701-714
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    • 2020
  • Quantitative high throughput screening (qHTS) assays are used to assess toxicity for many chemicals in a short period by collectively analyzing them at several concentrations. Data are routinely analyzed using nonlinear regression models; however, we propose a new method to analyze qHTS data using a nonlinear mixed effects model. qHTS data are generated by repeating the same experiment several times for each chemical; therefor, they can be viewed as if they are repeated measures data and hence analyzed using a nonlinear mixed effects model which accounts for both intra- and inter-individual variabilities. Furthermore, we apply a one-step approach incorporating robust estimation methods to estimate fixed effect parameters and the variance-covariance structure since outliers or influential observations are not uncommon in qHTS data. The toxicity of chemicals from a qHTS assay is classified based on the significance of a parameter related to the efficacy of the chemicals using the proposed method. We evaluate the performance of the proposed method in terms of power and false discovery rate using simulation studies comparing with one existing method. The proposed method is illustrated using a dataset obtained from the National Toxicology Program.

Prediction MOdels for Channel Bed Evolution Due to Short Term Floods (단기간의 홍수에 의한 하상변동의 예측모형)

  • Pyo, Yeong-Pyeong;Sin, Cheol-Sik;Bae, Yeol-Ho
    • Journal of Korea Water Resources Association
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    • v.30 no.6
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    • pp.597-610
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    • 1997
  • One-dimensional numerical models using finite difference methods for unsteady sediment transport on alluvial river channel are developed. The Preissmann implicit scheme and the Lax-Wendroff two-step explicit scheme with the Method of Characteristics for water motion and a forward time centered space explicit scheme for sediment motion are developed to simulate the sediment transport rate and the variation of channel bed level. The program correctness of each model is successfully verified using volume conservation tests. The sensitivity studies show that higher peak stage level, steeper channel slope and longer flooding duration produce more channel bed erosion. and median grain size, $D_{50}=0.4mm$ give maximum volume loss in this study. Finally, the numerical models are found to produce reasonable results from the various sensitivity tests which reveal that the numerical models have properly responded to the changes of each model parameter.

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