Automatic forecasting with a modified exponential smoothing state space framework

A new automatic forecasting procedure is proposed based on a recent exponential smoothing framework which incorporates a Box-Cox transformation and ARMA residual corrections. The procedure is complete with well-defined methods for initialization, estimation, likelihood evaluation, and analytical derivation of point and interval predictions under a Gaussian error assumption. The algorithm is examined extensively by applying it to single seasonal and non-seasonal time series from the M and the M3 competitions, and is shown to provide competitive out-of-sample forecast accuracy compared to the best methods in these competitions and to the traditional exponential smoothing framework. The proposed algorithm can be used as an alternative to existing automatic forecasting procedures in modeling single seasonal and non-seasonal time series. In addition, it provides the new option of automatic modeling of multiple seasonal time series which cannot be handled using any of the existing automatic forecasting procedures. The proposed automatic procedure is further illustrated by applying it to two multiple seasonal time series involving call center data and electricity demand data.Exponential smoothing, state space models, automatic forecasting, Box-Cox transformation, residual adjustment, multiple seasonality, time series

Forecasting time series with complex seasonal patterns using exponential smoothing

A new innovations state space modeling framework, incorporating Box-Cox transformations, Fourier series with time varying coefficients and ARMA error correction, is introduced for forecasting complex seasonal time series that cannot be handled using existing forecasting models. Such complex time series include time series with multiple seasonal periods, high frequency seasonality, non-integer seasonality and dual-calendar effects. Our new modelling framework provides an alternative to existing exponential smoothing models, and is shown to have many advantages. The methods for initialization and estimation, including likelihood evaluation, are presented, and analytical expressions for point forecasts and interval predictions under the assumption of Gaussian errors are derived, leading to a simple, comprehensible approach to forecasting complex seasonal time series. Our trigonometric formulation is also presented as a means of decomposing complex seasonal time series, which cannot be decomposed using any of the existing decomposition methods. The approach is useful in a broad range of applications, and we illustrate its versatility in three empirical studies where it demonstrates excellent forecasting performance over a range of prediction horizons. In addition, we show that our trigonometric decomposition leads to the identification and extraction of seasonal components, which are otherwise not apparent in the time series plot itself.Exponential smoothing, Fourier series, prediction intervals, seasonality, state space models, time series decomposition

Religion, State, and a Conflict of Duties:A Constitutional Problem in Sri Lanka

Both of Sri Lanka’s post-independence, autochthonous, republican constitutions have contained within their pages a directive which declares that “Buddhism shall have foremost place”. The framers of Sri Lanka’s constitution insisted that this was simply an acknowledgement of the “special” place of Buddhism in the fabric of Sri Lanka’s history. However, recent history has shown this provision being used directly and indirectly to deny portions of Sri Lankans their fundamental rights. The victims of this provision belong both to the majority and minority religions. The question this thesis attempted to answer was: does Sri Lanka’s duty to Buddhism under Article 9 of the Constitution conflict with its duties to its citizens under fundamental rights provisions? This thesis argues that (i) such a conflict does exist and (ii) where it arises the state has time after time prioritized the promotion and protection of Buddhism over protecting its citizens’ fundamental rights, and that this has in turn affected the state’s ability to deal neutrally with its citizens. Four instances of this conflict are examined in detail: the restrictions placed on proselytization, the Deeghavapi case, the child monk and the re-imposition of a ban on women’s ability to purchase alcohol. This thesis further argues that legal and political protections afforded to religious minorities, such as personal laws and special laws are insufficient to protect the rights of vulnerable groups within those minorities and instead serve to promote communalism

Impact of Corporate Incentives of Finance Managers on Financial Performance of Public Listed Companies in Sri Lanka

In the context of improving financial performance of companies throughout the world, corporate incentives provided to finance managers with respect to enhanced employee performance is of paramount importance. However, this paper is based on the findings of public listed companies in Sri Lanka. Even though theories to satisfy and motivate employees through corporate incentives have been extensively studied, most researchers do have different views on major predictions on financial performance of listed companies. This paper aims to ascertain the adequacy and the level of corporate incentives of finance managers required to enhance financial performance of public listed companies in Sri Lanka. For the purpose of investigation, a quantitative study with the use of deductive method, using stratified random sampling technique consisting a sample of 200 Public Listed Companies out of a population of 306 was used. Both primary data sourced through questionnaires from the representative sample of the population and secondary data available in the annual reports of listed firms within last 5 years were used to conduct multiple correlation and regression analysis. The obtained results were relatively according to the literature developed in the study as expounded by Fredrick Herzberg under Two Factor Theory and also by Alderfer under ERG theory. The results indicated corporate incentives have a strong effect on financial performance and a strong relationship between corporate incentives with financial performance of listed firms. Corporate incentives in the context of factors of motivation were more effective than hygiene factors as explained by Herzberg and also by Alderfer which the theoretical framework was based upon in this study. This study recommended that public listed companies in the Colombo Stock Exchange should focus on intrinsic corporate incentives (factors of motivation) as emphasized by Herzberg than extrinsic corporate incentives (hygiene factors). This study implied that Human Resource practitioners, theorists, researchers and remuneration policy makers to consider requisite level of corporate incentives to formulate remuneration policies and procedures to mitigate, avoid and prevent discrepancies in incentive anomalies to motivate finance managers to gain successful financial growth. Keywords: Anomalies, Deductive Method, Financial Performance, Hygiene Factors, Sample Siz

PENERAPAN METODE ANALYTICAL HIERARCHY PROCESS (AHP) UNTUK MEMBANGUN SISTEM PENDUKUNG KEPUTUSAN DALAM MENENTUKAN SASARAN REHABILITASI SOSIAL TERPADU BAGI PENYANDANG DISABILITAS

Dinas Sosial Provinsi Sumatera Barat merupakan salah satu lembaga pemerintahan yang memiliki beberapa program dan layanan pemberian bantuan kepada masyarakat dimana harus diberikan kepada penerima yang layak dan pantas untuk mendapatkannya. Salah satu bentuk program dan layanan yang diberikan oleh Dinas Sosial adalah rehabilitasi sosial terpadu bagi penyandang disabilitas. Namun dalam pelaksanaannya masih belum terlaksana secara optimal sehingga timbul beberapa permasalahan dalam menentukan penerima rehabilitasi sosial seperti kerugian bagi para penyandang disabilitas yang seharusya diprioritaskan untuk menerima rehabilitasi pada periode tersebut namun tidak diprioritaskan dan harus menunggu pada periode selanjutnya sehingga menyebabkan rehabilitasi sosial tidak terdistribusi dengan baik dan tidak tepat sasaran terhadap calon penerima yang seharusnya menerima rehabilitasi sosial pada periode waktu tersebut. Selain itu, proses pengumpulan data yang masih dilakukan secara manual akan menyebabkan terjadinya kesalahan dalam memproses banyak data kriteria bagi calon penerima dalam memperoleh bantuan. Beberapa permasalahan tersebut diketahui Ketika melakukan wawancara dengan kepala bidang rehabilitasi sosial. Sehingga hal inilah yang menjadi dasar dilakukannya penelitian ini dengan tujuan untuk membangun Sistem Pendukung Keputusan dengan menerapkan metode Analytical Hierarchy Process (AHP) dalam menentukan sasaran penerima rehabilitasi sosial terpadu bagi Penyandang Disabilitas. Alasan dipilihnya metode Analytical Hierarchy Process (AHP) dikarenakan metode ini memiliki struktur hierarki yang dapat membantu pengambil keputusan untuk mengetahui alternatif terbaik dari banyaknya elemen pilihan dengan menggunakan perbandingan berpasangan (pair wise comparison) untuk membuat suatu matriks yang menggambarkan perbandingan antara elemen yang satu dengan elemen yang lainnya. Sehingga pengambilan keputusan dapat menjadi lebih kompleks karena adanya pelibatan beberapa tujuan maupun kriteria yang selaras. Dengan adanya Sistem Penunjang Keputusan ini dapat menjadi salah satu solusi dalam menyelesaikan permasalahan mengenai penentuan sasaran rehabilitasi sosial terpadu bagi Penyandang Disabilitas agar menjadi lebih tepat sasaran

El catálogo del paisaje agrario de la Ex Hacienda de Chapingo: un instrumento para su apreciación y salvaguarda

230 páginas. Maestría en Diseño.La ex hacienda de Chapingo, hoy universidad, inició como respuesta a la visión de construcción del país relacionada con la labor formativa de la producción agrícola, pecuaria y forestal, posee una belleza producto del acumulado histórico de su edificación y conforma un patrimonio arquitectónico único, donde los valores del campus están en sus inmuebles, pero también se encuentran en los elementos ambientales y las áreas verdes, los cuerpos de agua y el paisaje de sus campos agrícolas, es decir, su paisaje agrario. En ese contexto, la zona se encuentra inmersa en una región cuyo desarrollo demográfico e inmobiliario ha provocado una urbanización descontrolada del entorno, donde la reducción de la superficie agrícola tiene gran trascendencia para el futuro de estos espacios, por ello es necesaria una investigación a profundidad que salvaguarde su carácter agropecuario, al considerar que no existen las directrices ni legislación necesarias para su adecuada preservación tanto de las edificaciones, como de sus espacios abiertos, se plantea la puesta en valor de estos paisajes mediante nuevas metodologías como el inventario y catálogo, que faciliten su comprensión y clasificación para determinar su calidad monumental y ambiental, sustentabilidad, riqueza cultural, productiva e histórica.The “ex hacienda de Chapingo”, now university, is a response to the vision of construction of the country related to the formative labor of the agricultural, cattle and forest production, which possesses a beauty product of the historical accumulated of its building, shaping a unique architectural heritage, where the values of the campus are in this real-estate, but also they are in the environmental elements, the green areas, the water and the cultivated landscape of its agricultural fields. In this context Chapingo is immersed in a region which demographic and real-estate development has provoked an uncontrolled urbanization of the environment, where the reduction of the agricultural surface is important for the future of these spaces, due to is necessary a deep research to protect the character of the ex-estate and agricultural institution, marking the directives for an appropriate preservation of the buildings as well as of its spaces, by new methodologies that facilitate its comprehension and classification as the inventory and rural landscape catalogue to determine its monumental and environmental quality, sustainability, production, historical and cultural richness

The Kodaly Method: A Vocal Approach to Music Education

An examination of the Kodaly Method for music education

Application of Discrete-Interval Moving Seasonalities to Spanish Electricity Demand Forecasting during Easter

[EN] Forecasting electricity demand through time series is a tool used by transmission system operators to establish future operating conditions. The accuracy of these forecasts is essential for the precise development of activity. However, the accuracy of the forecasts is enormously subject to the calendar effect. The multiple seasonal Holt-Winters models are widely used due to the great precision and simplicity that they offer. Usually, these models relate this calendar effect to external variables that contribute to modification of their forecasts a posteriori. In this work, a new point of view is presented, where the calendar effect constitutes a built-in part of the Holt-Winters model. In particular, the proposed model incorporates discrete-interval moving seasonalities. Moreover, a clear example of the application of this methodology to situations that are difficult to treat, such as the days of Easter, is presented. The results show that the proposed model performs well, outperforming the regular Holt-Winters model and other methods such as artificial neural networks and Exponential Smoothing State Space Model with Box-Cox Transformation, ARMA Errors, Trend and Seasonal Components (TBATS) methods.The authors would like to thank the Spanish Ministry of Economy and Competitiveness for the support under project TIN2017-8888209C2-1-R.Trull, Ó.; García-Díaz, JC.; Troncoso, A. (2019). Application of Discrete-Interval Moving Seasonalities to Spanish Electricity Demand Forecasting during Easter. Energies. 12(6):1-16. https://doi.org/10.3390/en12061083S116126Garrués-Irurzun, J., & López-García, S. (2009). Red Eléctrica de España S.A.: Instrument of regulation and liberalization of the Spanish electricity market (1944–2004). Renewable and Sustainable Energy Reviews, 13(8), 2061-2069. doi:10.1016/j.rser.2009.01.028Roldan-Fernandez, J., Gómez-Quiles, C., Merre, A., Burgos-Payán, M., & Riquelme-Santos, J. (2018). Cross-Border Energy Exchange and Renewable Premiums: The Case of the Iberian System. Energies, 11(12), 3277. doi:10.3390/en11123277Contreras, J., Espinola, R., Nogales, F. J., & Conejo, A. J. (2003). ARIMA models to predict next-day electricity prices. IEEE Transactions on Power Systems, 18(3), 1014-1020. doi:10.1109/tpwrs.2002.804943Juberias, G., Yunta, R., Garcia Moreno, J., & Mendivil, C. (1999). A new ARIMA model for hourly load forecasting. 1999 IEEE Transmission and Distribution Conference (Cat. No. 99CH36333). doi:10.1109/tdc.1999.755371Bianco, V., Manca, O., & Nardini, S. (2009). Electricity consumption forecasting in Italy using linear regression models. Energy, 34(9), 1413-1421. doi:10.1016/j.energy.2009.06.034Taylor, J. W. (2003). Short-term electricity demand forecasting using double seasonal exponential smoothing. Journal of the Operational Research Society, 54(8), 799-805. doi:10.1057/palgrave.jors.2601589Taylor, J. W. (2010). Triple seasonal methods for short-term electricity demand forecasting. European Journal of Operational Research, 204(1), 139-152. doi:10.1016/j.ejor.2009.10.003Ko, C.-N., & Lee, C.-M. (2013). Short-term load forecasting using SVR (support vector regression)-based radial basis function neural network with dual extended Kalman filter. Energy, 49, 413-422. doi:10.1016/j.energy.2012.11.015Rana, M., & Koprinska, I. (2016). Forecasting electricity load with advanced wavelet neural networks. Neurocomputing, 182, 118-132. doi:10.1016/j.neucom.2015.12.004Baliyan, A., Gaurav, K., & Mishra, S. K. (2015). A Review of Short Term Load Forecasting using Artificial Neural Network Models. Procedia Computer Science, 48, 121-125. doi:10.1016/j.procs.2015.04.160Yang, Z., Ce, L., & Lian, L. (2017). Electricity price forecasting by a hybrid model, combining wavelet transform, ARMA and kernel-based extreme learning machine methods. Applied Energy, 190, 291-305. doi:10.1016/j.apenergy.2016.12.130Ghadimi, N., Akbarimajd, A., Shayeghi, H., & Abedinia, O. (2018). Two stage forecast engine with feature selection technique and improved meta-heuristic algorithm for electricity load forecasting. Energy, 161, 130-142. doi:10.1016/j.energy.2018.07.088Troncoso Lora, A., Riquelme Santos, J. M., Riquelme, J. C., Gómez Expósito, A., & Martínez Ramos, J. L. (2004). Time-Series Prediction: Application to the Short-Term Electric Energy Demand. Lecture Notes in Computer Science, 577-586. doi:10.1007/978-3-540-25945-9_57Martinez Alvarez, F., Troncoso, A., Riquelme, J. C., & Aguilar Ruiz, J. S. (2011). Energy Time Series Forecasting Based on Pattern Sequence Similarity. IEEE Transactions on Knowledge and Data Engineering, 23(8), 1230-1243. doi:10.1109/tkde.2010.227Cancelo, J. R., Espasa, A., & Grafe, R. (2008). Forecasting the electricity load from one day to one week ahead for the Spanish system operator. International Journal of Forecasting, 24(4), 588-602. doi:10.1016/j.ijforecast.2008.07.005TORRÓ, H., MENEU, V., & VALOR, E. (2003). Single Factor Stochastic Models with Seasonality Applied to Underlying Weather Derivatives Variables. The Journal of Risk Finance, 4(4), 6-17. doi:10.1108/eb022969Darbellay, G. A., & Slama, M. (2000). Forecasting the short-term demand for electricity. International Journal of Forecasting, 16(1), 71-83. doi:10.1016/s0169-2070(99)00045-xMoral-Carcedo, J., & Vicéns-Otero, J. (2005). Modelling the non-linear response of Spanish electricity demand to temperature variations. Energy Economics, 27(3), 477-494. doi:10.1016/j.eneco.2005.01.003Erişen, E., Iyigun, C., & Tanrısever, F. (2017). Short-term electricity load forecasting with special days: an analysis on parametric and non-parametric methods. Annals of Operations Research. doi:10.1007/s10479-017-2726-6Arora, S., & Taylor, J. W. (2013). Short-Term Forecasting of Anomalous Load Using Rule-Based Triple Seasonal Methods. IEEE Transactions on Power Systems, 28(3), 3235-3242. doi:10.1109/tpwrs.2013.2252929Arora, S., & Taylor, J. W. (2018). Rule-based autoregressive moving average models for forecasting load on special days: A case study for France. European Journal of Operational Research, 266(1), 259-268. doi:10.1016/j.ejor.2017.08.056Bermúdez, J. D. (2013). Exponential smoothing with covariates applied to electricity demand forecast. European J. of Industrial Engineering, 7(3), 333. doi:10.1504/ejie.2013.054134Göb, R., Lurz, K., & Pievatolo, A. (2013). Electrical load forecasting by exponential smoothing with covariates. Applied Stochastic Models in Business and Industry, 29(6), 629-645. doi:10.1002/asmb.2008Chatfield, C. (1978). The Holt-Winters Forecasting Procedure. Applied Statistics, 27(3), 264. doi:10.2307/234716