In this paper, the Holt’s exponential smoothing and Auto-Regressive Integrated Moving Average (ARIMA) models were used to forecast inflation rate of Zambia using the monthly consumer price index (CPI) data from May 2...In this paper, the Holt’s exponential smoothing and Auto-Regressive Integrated Moving Average (ARIMA) models were used to forecast inflation rate of Zambia using the monthly consumer price index (CPI) data from May 2010 to May 2014. Results show that the ARIMA ((12), 1, 0) is an adequate model which best fits the CPI time series data and is therefore suitable for forecasting CPI and subsequently the inflation rate. However, the choice of the Holt’s exponential smoothing is as good as an ARIMA model considering the smaller deviations in the mean absolute percentage error and mean square error. Moreover, the Holt’s exponential smoothing model is less complicated since you do not require specialised software to implement it as is the case for ARIMA models. The forecasted inflation rate for April and May, 2015 is 7.0 and 6.6 respectively.展开更多
In the investigation of disease dynamics, the effect of covariates on the hazard function is a major topic. Some recent smoothed estimation methods have been proposed, both frequentist and Bayesian, based on the relat...In the investigation of disease dynamics, the effect of covariates on the hazard function is a major topic. Some recent smoothed estimation methods have been proposed, both frequentist and Bayesian, based on the relationship between penalized splines and mixed models theory. These approaches are also motivated by the possibility of using automatic procedures for determining the optimal amount of smoothing. However, estimation algorithms involve an analytically intractable hazard function, and thus require ad-hoc software routines. We propose a more user-friendly alternative, consisting in regularized estimation of piecewise exponential models by Bayesian P-splines. A further facilitation is that widespread Bayesian software, such as WinBUGS, can be used. The aim is assessing the robustness of this approach with respect to different prior functions and penalties. A large dataset from breast cancer patients, where results from validated clinical studies are available, is used as a benchmark to evaluate the reliability of the estimates. A second dataset from a small case series of sarcoma patients is used for evaluating the performances of the PE model as a tool for exploratory analysis. Concerning breast cancer data, the estimates are robust with respect to priors and penalties, and consistent with clinical knowledge. Concerning soft tissue sarcoma data, the estimates of the hazard function are sensitive with respect to the prior for the smoothing parameter, whereas the estimates of regression coefficients are robust. In conclusion, Gibbs sampling results an efficient computational strategy. The issue of the sensitivity with respect to the priors concerns only the estimates of the hazard function, and seems more likely to occur when non-large case series are investigated, calling for tailored solutions.展开更多
The hydrological system in Central Asia is highly sensitive to global climate change,significantly affecting water supply and energy production.In Tajikistan,the Vakhsh River—one of the main tributaries of the Amu Da...The hydrological system in Central Asia is highly sensitive to global climate change,significantly affecting water supply and energy production.In Tajikistan,the Vakhsh River—one of the main tributaries of the Amu Darya—plays a key role in the region’s hydropower and irrigation.However,research on long-term hydrological changes in its two top large basins—the Surkhob and Khingov river basins—remains limited.Therefore,this study analyzed long-term climate and hydrological changes in the Vakhsh River,including its main tributaries—the Surkhob and Khingov rivers—which are vital for the water resource management in Tajikistan and even in Central Asia.Using long-term hydrometeorological observations,the change trends of temperature(1933–2020),precipitation(1970–2020),and runoff(1940–2018)were examined to assess the impact of climate change on the regional water resources.The analysis revealed the occurrence of significant warming and a spatially uneven increase in precipitation.The temperature changes across three climatic periods(1933–1960,1960–1990,and 1990–2020)indicated that there was a transition from baseline level to accelerated warming.The precipitation showed a 2.99 mm/a increase in the Khingov River Basin and a 2.80 mm/a increase in the Surkhob River Basin during 1970–2020.Moreover,there was a gradual shift toward wetter conditions in recent decades.Despite the relatively stable annual mean runoff,seasonal redistribution occurred,with increased runoff in spring and reduced runoff in summer,due to the compensation of glacier melting.Moreover,this study forecasted runoff change during 2019–2040 using the exponential triple smoothing(ETS)method and revealed the occurrence of alternating wet and dry phases,emphasizing the sensitivity of the Vakhsh River Basin’s hydrological system to climate change and the necessity of adaptive water resource management in mountainous regions of Central Asia.Therefore,this study can provide evidence-based insights that are critical for future water resources planning,climate-resilient hydropower development,and regional adaptation strategies in climate-vulnerable basins in Central Asia.展开更多
基金Supported by National High Technology Research and Development Program of China （863 Program） （2007AA11Z221）, International Cooperation Project of Shanghai （08210707500）, and Natural Science Foundation of Shanghai.（08ZR1420600） . _
文摘In this paper, the Holt’s exponential smoothing and Auto-Regressive Integrated Moving Average (ARIMA) models were used to forecast inflation rate of Zambia using the monthly consumer price index (CPI) data from May 2010 to May 2014. Results show that the ARIMA ((12), 1, 0) is an adequate model which best fits the CPI time series data and is therefore suitable for forecasting CPI and subsequently the inflation rate. However, the choice of the Holt’s exponential smoothing is as good as an ARIMA model considering the smaller deviations in the mean absolute percentage error and mean square error. Moreover, the Holt’s exponential smoothing model is less complicated since you do not require specialised software to implement it as is the case for ARIMA models. The forecasted inflation rate for April and May, 2015 is 7.0 and 6.6 respectively.
文摘In the investigation of disease dynamics, the effect of covariates on the hazard function is a major topic. Some recent smoothed estimation methods have been proposed, both frequentist and Bayesian, based on the relationship between penalized splines and mixed models theory. These approaches are also motivated by the possibility of using automatic procedures for determining the optimal amount of smoothing. However, estimation algorithms involve an analytically intractable hazard function, and thus require ad-hoc software routines. We propose a more user-friendly alternative, consisting in regularized estimation of piecewise exponential models by Bayesian P-splines. A further facilitation is that widespread Bayesian software, such as WinBUGS, can be used. The aim is assessing the robustness of this approach with respect to different prior functions and penalties. A large dataset from breast cancer patients, where results from validated clinical studies are available, is used as a benchmark to evaluate the reliability of the estimates. A second dataset from a small case series of sarcoma patients is used for evaluating the performances of the PE model as a tool for exploratory analysis. Concerning breast cancer data, the estimates are robust with respect to priors and penalties, and consistent with clinical knowledge. Concerning soft tissue sarcoma data, the estimates of the hazard function are sensitive with respect to the prior for the smoothing parameter, whereas the estimates of regression coefficients are robust. In conclusion, Gibbs sampling results an efficient computational strategy. The issue of the sensitivity with respect to the priors concerns only the estimates of the hazard function, and seems more likely to occur when non-large case series are investigated, calling for tailored solutions.
基金supported by the National Natural Science Foundation of China(W2412135).
文摘The hydrological system in Central Asia is highly sensitive to global climate change,significantly affecting water supply and energy production.In Tajikistan,the Vakhsh River—one of the main tributaries of the Amu Darya—plays a key role in the region’s hydropower and irrigation.However,research on long-term hydrological changes in its two top large basins—the Surkhob and Khingov river basins—remains limited.Therefore,this study analyzed long-term climate and hydrological changes in the Vakhsh River,including its main tributaries—the Surkhob and Khingov rivers—which are vital for the water resource management in Tajikistan and even in Central Asia.Using long-term hydrometeorological observations,the change trends of temperature(1933–2020),precipitation(1970–2020),and runoff(1940–2018)were examined to assess the impact of climate change on the regional water resources.The analysis revealed the occurrence of significant warming and a spatially uneven increase in precipitation.The temperature changes across three climatic periods(1933–1960,1960–1990,and 1990–2020)indicated that there was a transition from baseline level to accelerated warming.The precipitation showed a 2.99 mm/a increase in the Khingov River Basin and a 2.80 mm/a increase in the Surkhob River Basin during 1970–2020.Moreover,there was a gradual shift toward wetter conditions in recent decades.Despite the relatively stable annual mean runoff,seasonal redistribution occurred,with increased runoff in spring and reduced runoff in summer,due to the compensation of glacier melting.Moreover,this study forecasted runoff change during 2019–2040 using the exponential triple smoothing(ETS)method and revealed the occurrence of alternating wet and dry phases,emphasizing the sensitivity of the Vakhsh River Basin’s hydrological system to climate change and the necessity of adaptive water resource management in mountainous regions of Central Asia.Therefore,this study can provide evidence-based insights that are critical for future water resources planning,climate-resilient hydropower development,and regional adaptation strategies in climate-vulnerable basins in Central Asia.
