Pub Date : 2021-08-11DOI: 10.1080/23737484.2021.1942326
Tatiana Tambouratzis, Vassileios Canellidis, M. Chalikias
Abstract An assortment of evolutionary strategies (EvSs) is put forward for guiding interested countries toward the maximization of their environmental sustainability (ES), as demonstrated on the “landmark” Environmental Sustainability Index (ESI) 2005. The EvSs employ: (a) as inputs/chromosomes, the sets of ESI constructs which have been established as significant as well as sufficient in determining country ES; (b) as output, the singleton ESI 2005 scores which express the levels of ES attained by the participating countries; (c) as fitness function, the most accurate first degree (according to the primary literature) polynomials linking (a) and (b); and (d) realistic quasi-monotonic ES improvements, implemented via the application of exclusively positive mutations to the selected genes of each next-generation chromosome and the subsequent changes made to the remaining genes, with the sign and magnitude of each change being determined by the cross-correlation (CC) coefficients between the set of mutated genes and each remaining gene of the new chromosome. The created EvSs cover all the direct and stepwise approximations linking constructs and scores, thus offering alternative paths toward attaining maximal ES. Future research shall focus upon the selection of the EvS which affords maximal ES improvement at each generation.
{"title":"Realizable and adaptive maximization of environmental sustainability at the country level using evolutionary strategies","authors":"Tatiana Tambouratzis, Vassileios Canellidis, M. Chalikias","doi":"10.1080/23737484.2021.1942326","DOIUrl":"https://doi.org/10.1080/23737484.2021.1942326","url":null,"abstract":"Abstract An assortment of evolutionary strategies (EvSs) is put forward for guiding interested countries toward the maximization of their environmental sustainability (ES), as demonstrated on the “landmark” Environmental Sustainability Index (ESI) 2005. The EvSs employ: (a) as inputs/chromosomes, the sets of ESI constructs which have been established as significant as well as sufficient in determining country ES; (b) as output, the singleton ESI 2005 scores which express the levels of ES attained by the participating countries; (c) as fitness function, the most accurate first degree (according to the primary literature) polynomials linking (a) and (b); and (d) realistic quasi-monotonic ES improvements, implemented via the application of exclusively positive mutations to the selected genes of each next-generation chromosome and the subsequent changes made to the remaining genes, with the sign and magnitude of each change being determined by the cross-correlation (CC) coefficients between the set of mutated genes and each remaining gene of the new chromosome. The created EvSs cover all the direct and stepwise approximations linking constructs and scores, thus offering alternative paths toward attaining maximal ES. Future research shall focus upon the selection of the EvS which affords maximal ES improvement at each generation.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"7 1","pages":"590 - 623"},"PeriodicalIF":0.0,"publicationDate":"2021-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86503334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-02DOI: 10.1080/23737484.2021.1958272
M. Dimitrov, Lu Jin, Ying Ni
Abstract In this article, a model under which the underlying asset follows a Markov regime-switching process is considered. The underlying economy is partially observable in a form of a signal stochastically related to the actual state of the economy. The American option pricing problem is formulated using a partially observable Markov decision process (POMDP). Through the article, a three-state economy is assumed with a focus on the threshold for the early exercise, hold regions and its monotonicity. An extensive numerical experimental study is conducted in order to clarify the relationship between the monotonicity of the exercising strategy and the sufficient conditions which are obtained in Jin, Dimitrov, and Ni. In this article, the effect of sufficient conditions is confirmed. It was shown that sufficient conditions are not necessary for the monotonicity of the exercising strategy, and a discussion including milder conditions is presented based on the numerical studies.
{"title":"Properties of American options under a Markovian Regime Switching Model","authors":"M. Dimitrov, Lu Jin, Ying Ni","doi":"10.1080/23737484.2021.1958272","DOIUrl":"https://doi.org/10.1080/23737484.2021.1958272","url":null,"abstract":"Abstract In this article, a model under which the underlying asset follows a Markov regime-switching process is considered. The underlying economy is partially observable in a form of a signal stochastically related to the actual state of the economy. The American option pricing problem is formulated using a partially observable Markov decision process (POMDP). Through the article, a three-state economy is assumed with a focus on the threshold for the early exercise, hold regions and its monotonicity. An extensive numerical experimental study is conducted in order to clarify the relationship between the monotonicity of the exercising strategy and the sufficient conditions which are obtained in Jin, Dimitrov, and Ni. In this article, the effect of sufficient conditions is confirmed. It was shown that sufficient conditions are not necessary for the monotonicity of the exercising strategy, and a discussion including milder conditions is presented based on the numerical studies.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"32 1","pages":"573 - 589"},"PeriodicalIF":0.0,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85524197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-03DOI: 10.1080/23737484.2021.1964407
A. Rosenblad
Abstract This study compared the accuracy of automatic time series forecasting methods in predicting the results of the 2018 Swedish general election using data from the Party Preference Survey opinion poll collected during the years 1984–2018. The general exponential smoothing state space (ETS) model performed best, outperforming even the exit poll collected at the time of the election, while the complex seasonal autoregressive integrated moving average (ARIMA) model was beaten by the simple exponential smoothing method. Holt’s linear trend method performed worse than even the naïve method. The results of this study show the usefulness of easily applied automatic forecasting methods.
{"title":"Accuracy of automatic forecasting methods for univariate time series data: A case study predicting the results of the 2018 Swedish general election using decades-long data series","authors":"A. Rosenblad","doi":"10.1080/23737484.2021.1964407","DOIUrl":"https://doi.org/10.1080/23737484.2021.1964407","url":null,"abstract":"Abstract This study compared the accuracy of automatic time series forecasting methods in predicting the results of the 2018 Swedish general election using data from the Party Preference Survey opinion poll collected during the years 1984–2018. The general exponential smoothing state space (ETS) model performed best, outperforming even the exit poll collected at the time of the election, while the complex seasonal autoregressive integrated moving average (ARIMA) model was beaten by the simple exponential smoothing method. Holt’s linear trend method performed worse than even the naïve method. The results of this study show the usefulness of easily applied automatic forecasting methods.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"8 1","pages":"475 - 493"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84582903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-03DOI: 10.1080/23737484.2021.1952493
Talha Omer, P. Sjölander, K. Månsson, B. G. Kibria
Abstract In this article, we propose Liu-type shrinkage estimators for the zero-inflated Poisson regression (ZIPR) model in the presence of multicollinearity. Our new approach is a remedy to the problem of inflated variances for the ML estimation technique—which is a standard approach to estimate these types of count data models. When the data are in the form of non-negative integers with a surplus of zeros it induces overdispersion in the dependent variable. Considerable multicollinearity is frequently observed, but usually disregarded, for these types of data sets. Based on a Monte Carlo study we illustrate that our proposed estimators exhibit better MSE and MAE than the usual ML estimator and some other Liu estimators in the presence of multicollinearity. To demonstrate the advantages and the empirical relevance of our improved estimators, maternal death data are analyzed and the results illustrate similar benefits as is demonstrated in our simulation study.
{"title":"Improved estimators for the zero-inflated Poisson regression model in the presence of multicollinearity: simulation and application of maternal death data","authors":"Talha Omer, P. Sjölander, K. Månsson, B. G. Kibria","doi":"10.1080/23737484.2021.1952493","DOIUrl":"https://doi.org/10.1080/23737484.2021.1952493","url":null,"abstract":"Abstract In this article, we propose Liu-type shrinkage estimators for the zero-inflated Poisson regression (ZIPR) model in the presence of multicollinearity. Our new approach is a remedy to the problem of inflated variances for the ML estimation technique—which is a standard approach to estimate these types of count data models. When the data are in the form of non-negative integers with a surplus of zeros it induces overdispersion in the dependent variable. Considerable multicollinearity is frequently observed, but usually disregarded, for these types of data sets. Based on a Monte Carlo study we illustrate that our proposed estimators exhibit better MSE and MAE than the usual ML estimator and some other Liu estimators in the presence of multicollinearity. To demonstrate the advantages and the empirical relevance of our improved estimators, maternal death data are analyzed and the results illustrate similar benefits as is demonstrated in our simulation study.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"26 1","pages":"394 - 412"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87535602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-03DOI: 10.1080/23737484.2021.1952492
M. Malik
Abstract Age structure is crucial to various socio-economic and demographic factors. Better age quality data are critical to determine the reliability of large scale household surveys and the estimates they provide. Considering the importance and large sample these household surveys represent, we examined one of India’s largest household survey (NFHS) to determine its data quality and accuracy. Using multiple indices we also made a comparison of various age reporting measures to assess pattern of age heaping. Our results found that age heaping is a gray concern for household surveys in India. Though there has been some improvement, but over all age quality data are still very rough, affecting likely the survey estimates. Females are performing better on contrary to what earlier studies have found, which is likely due to improving socio-cultural and living norms in Indian settings. It is clear that age preference can likely cause the substantial biases in demographic factors and survey estimates. Thus studies examining age structure or any such methods where age is significantly important should adjust the age bias before carrying out further analysis. Furthermore, a single approach for age adjustment techniques is must to improve the age quality data for better policy implications.
{"title":"Age heaping pattern and data quality: evidence from Indian Household Survey Data (1991–2016)","authors":"M. Malik","doi":"10.1080/23737484.2021.1952492","DOIUrl":"https://doi.org/10.1080/23737484.2021.1952492","url":null,"abstract":"Abstract Age structure is crucial to various socio-economic and demographic factors. Better age quality data are critical to determine the reliability of large scale household surveys and the estimates they provide. Considering the importance and large sample these household surveys represent, we examined one of India’s largest household survey (NFHS) to determine its data quality and accuracy. Using multiple indices we also made a comparison of various age reporting measures to assess pattern of age heaping. Our results found that age heaping is a gray concern for household surveys in India. Though there has been some improvement, but over all age quality data are still very rough, affecting likely the survey estimates. Females are performing better on contrary to what earlier studies have found, which is likely due to improving socio-cultural and living norms in Indian settings. It is clear that age preference can likely cause the substantial biases in demographic factors and survey estimates. Thus studies examining age structure or any such methods where age is significantly important should adjust the age bias before carrying out further analysis. Furthermore, a single approach for age adjustment techniques is must to improve the age quality data for better policy implications.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"11 1","pages":"382 - 393"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86638809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-03DOI: 10.1080/23737484.2021.1964406
Oluwadare O. Ojo, A. Adepoju
Abstract Multicollinearity brings obstacle to estimation of regression models. A major stumbling block of the most classical method of estimation of regression model is that it is indeterminate in the presence of extreme perfect multicollinearity. This study examined the impact of some macroeconomic variables on National savings of the Nigerian economy. Since majority of these macroeconomic variables are highly correlated, the use of classical methods may be disastrously inappropriate. Hence, the Bayesian analysis with conjugate priors are used to explore the relationship between the national savings and these correlated macroeconomic variables of Nigerian economy in order to effectively handle the problem of multicollinearity. The Bayesian method using the Zellner’s prior handled the problem of multicollinearity efficiently.
{"title":"Bayesian analysis of macroeconomic variables on national savings","authors":"Oluwadare O. Ojo, A. Adepoju","doi":"10.1080/23737484.2021.1964406","DOIUrl":"https://doi.org/10.1080/23737484.2021.1964406","url":null,"abstract":"Abstract Multicollinearity brings obstacle to estimation of regression models. A major stumbling block of the most classical method of estimation of regression model is that it is indeterminate in the presence of extreme perfect multicollinearity. This study examined the impact of some macroeconomic variables on National savings of the Nigerian economy. Since majority of these macroeconomic variables are highly correlated, the use of classical methods may be disastrously inappropriate. Hence, the Bayesian analysis with conjugate priors are used to explore the relationship between the national savings and these correlated macroeconomic variables of Nigerian economy in order to effectively handle the problem of multicollinearity. The Bayesian method using the Zellner’s prior handled the problem of multicollinearity efficiently.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"15 1","pages":"432 - 441"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82449868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-03DOI: 10.1080/23737484.2021.1959468
M. Mwangi, G. Verbeke, E. Njagi, S. Mwalili, Anna Ivanova, Z. Bukania, G. Molenberghs
Abstract Repeated measures data are commonly encountered in a wide variety of disciplines including business, agriculture and medicine. The fact that observations from the same unit, in general, will not be independent poses particular challenges to the statistical procedures used for the analysis of such data. In the statistical literature, analysis of cross-over designs is mainly centred around a single response variable measured at the end of each period after treatment. Less commonly, cross-over design studies are used in more complex settings, for example, repeated measurements collected within each center across a number of centers or within individual’s treatment period(s). A single measurement response analysis approach may lead to loss of information that otherwise would be captured during patients follow-up, thus affecting precision in estimation. To circumvent this limitation, we propose the application of a piecewise linear mixed-effects model. We analyze data from a cross-over design, where both systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured repeatedly for each patient within each period. These are continuous variables assumed to arise from the family of Gaussian multivariate distributions. The objective of the study was to investigate changes in the two response variables over time and to detect the role of two treatment dosages of Iodine in household salt associated with a more rapid decrease in the two outcomes.
{"title":"Improved longitudinal data analysis for cross-over design settings, with a piecewise linear mixed-effects model","authors":"M. Mwangi, G. Verbeke, E. Njagi, S. Mwalili, Anna Ivanova, Z. Bukania, G. Molenberghs","doi":"10.1080/23737484.2021.1959468","DOIUrl":"https://doi.org/10.1080/23737484.2021.1959468","url":null,"abstract":"Abstract Repeated measures data are commonly encountered in a wide variety of disciplines including business, agriculture and medicine. The fact that observations from the same unit, in general, will not be independent poses particular challenges to the statistical procedures used for the analysis of such data. In the statistical literature, analysis of cross-over designs is mainly centred around a single response variable measured at the end of each period after treatment. Less commonly, cross-over design studies are used in more complex settings, for example, repeated measurements collected within each center across a number of centers or within individual’s treatment period(s). A single measurement response analysis approach may lead to loss of information that otherwise would be captured during patients follow-up, thus affecting precision in estimation. To circumvent this limitation, we propose the application of a piecewise linear mixed-effects model. We analyze data from a cross-over design, where both systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured repeatedly for each patient within each period. These are continuous variables assumed to arise from the family of Gaussian multivariate distributions. The objective of the study was to investigate changes in the two response variables over time and to detect the role of two treatment dosages of Iodine in household salt associated with a more rapid decrease in the two outcomes.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"80 1","pages":"413 - 431"},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83474281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-30DOI: 10.1080/23737484.2021.1936690
P. Giannouli, A. Karagrigoriou, Christos E. Kountzakis, Kimon Ntotsis
Abstract Several works concerning the modelling and the prediction of credit scoring have been made over time, based on features used in credit scoring, the effectiveness of different classification algorithms and also benchmarking studies classification algorithms for credit scoring. The objective of this work is the proposal of an innovative approach to flexible and accurate credit scoring modelling with the use of not only financial but also credit behavioural characteristics. In addition, we propose a multidimensional reduction algorithm in order to divulge the statistically significant variables that prevail and as an extension to create a reliable prediction model for credit scoring based on the effective combination of principal components analysis and regularization methods. The proposed novel procedure is applied to the Greek System separately for small and large enterprises with the use of a Credit Bureau database with more than 200,000 cases.
{"title":"Multilevel Dimension Reduction for Credit Scoring Modelling and Prediction: Empirical Evidence for Greece","authors":"P. Giannouli, A. Karagrigoriou, Christos E. Kountzakis, Kimon Ntotsis","doi":"10.1080/23737484.2021.1936690","DOIUrl":"https://doi.org/10.1080/23737484.2021.1936690","url":null,"abstract":"Abstract Several works concerning the modelling and the prediction of credit scoring have been made over time, based on features used in credit scoring, the effectiveness of different classification algorithms and also benchmarking studies classification algorithms for credit scoring. The objective of this work is the proposal of an innovative approach to flexible and accurate credit scoring modelling with the use of not only financial but also credit behavioural characteristics. In addition, we propose a multidimensional reduction algorithm in order to divulge the statistically significant variables that prevail and as an extension to create a reliable prediction model for credit scoring based on the effective combination of principal components analysis and regularization methods. The proposed novel procedure is applied to the Greek System separately for small and large enterprises with the use of a Credit Bureau database with more than 200,000 cases.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"134 1","pages":"545 - 560"},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77509909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-11DOI: 10.1080/23737484.2021.1929562
Cécile Spychala, Joël Armand, C. Dombry, C. Goga
Abstract Understanding and modeling road crash data is crucial in fulfilling safety goals by helping national authorities to take necessary measures to reduce crash frequency and severity. This work aims at giving a multivariate statistical analysis of road crash data from the French region of Franche-Comté with special attention to road crash gravity. The first step for this multivariate analysis was to perform multiple correspondence analysis in order to assess associations between the road crash injury and several important accident-related factors and circumstances. Log-linear models are used next in order to detect associations between road crash severity and related factors such as alcohol/drug consumption or spatial crash locations. The effects of each factors have been also evaluated on the road crash gravity by using ordinal logistic regression. Data used in this study are extracted from BAAC files, the French census of road crashes.
{"title":"Multivariate statistical analysis for exploring road crash-related factors in the Franche-Comté region of France","authors":"Cécile Spychala, Joël Armand, C. Dombry, C. Goga","doi":"10.1080/23737484.2021.1929562","DOIUrl":"https://doi.org/10.1080/23737484.2021.1929562","url":null,"abstract":"Abstract Understanding and modeling road crash data is crucial in fulfilling safety goals by helping national authorities to take necessary measures to reduce crash frequency and severity. This work aims at giving a multivariate statistical analysis of road crash data from the French region of Franche-Comté with special attention to road crash gravity. The first step for this multivariate analysis was to perform multiple correspondence analysis in order to assess associations between the road crash injury and several important accident-related factors and circumstances. Log-linear models are used next in order to detect associations between road crash severity and related factors such as alcohol/drug consumption or spatial crash locations. The effects of each factors have been also evaluated on the road crash gravity by using ordinal logistic regression. Data used in this study are extracted from BAAC files, the French census of road crashes.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"35 1","pages":"442 - 474"},"PeriodicalIF":0.0,"publicationDate":"2021-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81069349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-14DOI: 10.1080/23737484.2023.2217137
M. Puica, F. Benth
Abstract The share of wind power in fuel mixes worldwide has increased considerably. The main ingredient when deriving wind power predictions are wind speed data; the closer to the wind farms, the better they forecast the power supply. The current paper proposes a hybrid model for predicting wind speeds at convenient locations. It is then applied to Southern California power price area. We build random fields with time series of gridded historical forecasts and actual wind speed observations. We estimate with ordinary kriging the spatial variability of the temporal parameters and derive predictions. The advantages of this work are twofold: (1) an accurate daily wind speed forecast at any location in the area and (2) a general method applicable to other markets.
{"title":"A spatio-temporal model for predicting wind speeds in Southern California","authors":"M. Puica, F. Benth","doi":"10.1080/23737484.2023.2217137","DOIUrl":"https://doi.org/10.1080/23737484.2023.2217137","url":null,"abstract":"Abstract The share of wind power in fuel mixes worldwide has increased considerably. The main ingredient when deriving wind power predictions are wind speed data; the closer to the wind farms, the better they forecast the power supply. The current paper proposes a hybrid model for predicting wind speeds at convenient locations. It is then applied to Southern California power price area. We build random fields with time series of gridded historical forecasts and actual wind speed observations. We estimate with ordinary kriging the spatial variability of the temporal parameters and derive predictions. The advantages of this work are twofold: (1) an accurate daily wind speed forecast at any location in the area and (2) a general method applicable to other markets.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"75 1","pages":"321 - 349"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80378154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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