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Books on the topic 'Forecasting function'

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Published: 30 May 2022
Last updated: 31 May 2022

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1

Albertson, Kevin. Forecasting with a periodic transfer function model. Salford: University of Salford, Department of Economics, 1996.

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2

Albertson, Kevin. Forecasting with a periodic transfer function model. Salford: University of Salford, Department of Economics, 1996.

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3

Fildes, Robert. "Forecasting and loss functions". Fontainbleau: INSEAD, 1986.

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4

Ignacio, Rodríguez-Iturbe, ed. Random functions and hydrology. Reading, Mass: Addison-Wesley, 1985.

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5

Bras, Rafael L. Random functions and hydrology. New York: Dover Publications, 1993.

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6

Franke, Richard H. Covariance functions for statistical interpolation. Monterey, California: Naval Postgraduate School, 1986.

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7

Box, George E. P. Time series analysis: Forecasting and control. 4th ed. Hoboken, N.J: John Wiley, 2008.

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8

Box, George E. P. Time series analysis: Forecasting and control. 3rd ed. Englewood Cliffs, N.J: Prentice Hall, 1994.

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9

Box, George E. P. Time series analysis: Forecasting and control. 4th ed. Hoboken, N.J: John Wiley, 2008.

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10

Makridakis, Spyros. Exponential smoothing: The effect of initial values and loss functions on post-sample forecasting accuracy. Fontainbleau: INSEAD, 1990.

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11

Makridakis, Spyros. Exponential smoothing: The effect of initial values and loss functions on post-sample forecasting accuracy. Fontainbleau: INSEAD, 1991.

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12

Farrar, Robert M. Taper functions for predicting product volumes in natural shortleaf pines. New Orleans, La: U.S. Dept. of Agriculture, Forest Service, Southern Forest Experiment Station, 1987.

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13

Office, General Accounting. Budget issues: Fiscal year 1996 agency spending by budget function : report to the Honorable Richard K. Armey, Majority Leader, House of Representatives. Washington, D.C: The Office, 1997.

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14

Savchenko, Pol', Aleksandr Alekseev, Nikolay Ahapkin, Sergey Bobylev, Vladimir Varnavskiy, Aleksandr Vilenskiy, Grigoriy Goncharenko, et al. The Russian socio-economic system: realities and vectors of development. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1087982.

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The monograph reveals the System as a way of development of Russian society, as the balance of the whole and the parts at the macro-, meso - and micro-level, mathematical modeling of the System, freedom and justice, man as a factor of production human capital institutional framework for the development of Russian Systems of state and market regulation, improve planning and forecasting, digitalization, political institutions, social functions of the state, social capital, social trend, demography and family, motivation, labour and entrepreneurship, the institutions of labour market regulation, sustainable and dynamic development of the Russian System in the context of globalization. Of interest to researchers and practitioners, teachers, graduate students of economic specialties.
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15

Schnabel, Gert. Output trends and Okun's law. Basel, Switzerland: Bank for International Settlements, Monetary and Economic Dept., 2002.

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16

Xie tiao fa zhan quan mian ti sheng cheng shi gong neng: 2005 nian Shanghai jing ji fa zhan lan pi shu = Harmonious development, promotion of urban functions in all-round way : an economic development bluebook of Shanghai, 2005. Shanghai Shi: Shanghai she hui ke xue yuan chu ban she, 2005.

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17

Arora, Vivek. Potential output and total factor productivity growth in post-apartheid South Africa. Washington, D.C: International Monetary Fund, African Department, 2003.

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18

Cochrane, John H. Using production based asset pricing to explain the behavior of stock returns over the business cycle. Cambridge, MA: National Bureau of Economic Research, 1989.

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19

Chung, Edwin. A proposed intelligent bandwidth management system based on Turksen's Fuzzy Function approach using reinforcement learning forecasting. 2005.

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20

Chung, Edwin. A proposed intelligent bandwidth management system based on Turksen's Fuzzy Function approach using reinforcement learning forecasting. 2005.

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21

Posner, Paul L. Budget Issues: Fiscal Year 1996 Agency Spending by Budget Function. Diane Pub Co, 1997.

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22

Kondrakiewicz, Dariusz. Prognozowanie i symulacje międzynarodowe. Instytut Europy Środkowej, 2021. http://dx.doi.org/10.36874/m21580.

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International forecasting and simulation is a study that summarizes research, in a shortened and integrated version. The thematic scope concerns the basic terminology and methodological issues of forecasts and the forecasting process itself, forecasting institutions and the final product, i.e. international forecasts. The main goal is to present and systematize basic knowledge in the field of forecasting in international relations. The book is generally aimed at all those interested in international affairs. However, the author hopes that the publication will also be helpful for researchers and analysts dealing with difficult issues of international forecasting in the field of their scientific research methodologies. The work consists of two parts – theoretical and empirical. The theoretical part includes two chapters. The first chapter begins by discussing the concepts of forecasting and simulation. Next, considerations were made about the place of forecasting in science, pointing out the existing dilemmas in this regard, and also discussed categories, classifications and functions of forecasting and simulation. The second chapter presents the main elements of the forecast and the phases of the forecasting process. Most space was devoted to the presentation of the most important methods of forecasting in international relations, not limiting itself only to discussing them, but also assessing their usefulness for formulating international forecasts. In the third chapter, which is of an empirical nature, the selected forecasting institutions are first discussed according to the division applied into typically research, university, governmental, international and private institutions. This classification is of a contractual nature, but corresponds to the basic functions performed by individual institutions. In the further part of this chapter, the most important – according to the author – ecological, demographic and political forecasts are presented, focusing on discussing the main consequences of their possible implementation for international relations.
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23

Forecast Systems Laboratory (U.S.), ed. DARE hydrologic evaluations (1990-1992): Forecasters' assessment of functions. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Forecast Systems Laboratory, 1994.

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24

Forecast Systems Laboratory (U.S.), ed. DARE hydrologic evaluations (1990-1992): Forecasters' assessment of functions. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Forecast Systems Laboratory, 1994.

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25

Box, George E. P. Time Series Analysis: Forecasting & Control. Pearson Education Asia Limited, 2005.

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26

Jenkins, Gwilym M., Gregory C. Reinsel, and George E. P. Box. Time Series Analysis: Forecasting and Control. Wiley & Sons, Incorporated, John, 2011.

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27

Jenkins, Gwilym M., Gregory C. Reinsel, and George E. P. Box. Time Series Analysis: Forecasting and Control. Wiley & Sons, Incorporated, John, 2013.

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28

Jenkins, Gwilym M., Gregory C. Reinsel, George E. P. Box, and Greta M. Ljung. Time Series Analysis: Forecasting and Control. Wiley & Sons, Incorporated, John, 2015.

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29

Jenkins, Gwilym M., Gregory C. Reinsel, George E. P. Box, and Greta M. Ljung. Time Series Analysis: Forecasting and Control. Wiley & Sons, Incorporated, John, 2015.

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30

Time Series Analysis: Forecasting and Control. Wiley, 2015.

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31

Forecast Systems Laboratory (U.S.), ed. DARE hydrologic evaluations (1990-1992): Forecasters' assessment of functions. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Forecast Systems Laboratory, 1994.

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32

United States. National Aeronautics and Space Administration., ed. Investigations into the F-106 lightning strike environment as functions of altitude and storm phase. Rapid City, S.D: Institute of Atmospheric Sciences, South Dakota School of Mines and Technology, 1987.

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33

Box, George E. P. Time Series Analysis: Forecasting and Control (Wiley Series in Probability and Statistics). 4th ed. Wiley-Interscience, 2008.

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34

Mynbaev, Kairat T. Two essays in microeconomic theory and econometrics. 1995.

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35

Steven, Rosefielde, ed. Efficiency and Russia's economic recovery potential to the year 2000 and beyond. Aldershot, Hants, England: Ashgate, 1998.

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36

D, Hosek Susan, Rand Corporation, and United States. Health Care Financing Administration., eds. Charges and outcomes for rehabilitative care: Implications for the prospective payment system. Santa Monica, CA: Rand, 1986.

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37

Lopotenco, Viorica. DEVELOPMENT OF THE NEW INTERNATIONAL FINANCIAL ARCHITECTURE AT THE NATIONAL FINANCIAL SYSTEMS LEVEL. RS Global S. z O.O., 2020. http://dx.doi.org/10.31435/rsglobal/027.

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The fundamental purpose of this paper is to analyze the transformations in the international financial architecture and their impact on the national financial system. The analysis of the international financial architecture's functioning mechanism suggests its similarity with the software system structure. It is static in the way the system functionality is decomposed and divided into implementation teams. The efficiency of international financial architecture's functioning depends mainly on how balanced and interconnected its elements are. Thus, according to systems theory, only by overcoming the deformation of the international financial architecture at all its levels, it is possible to increase the financial system's overall performance. In this regard, maintaining a dynamic balance in the development of the international financial architecture as an integral unit of its structural elements and functions is becoming of urgent importance. This aspect of the research allows the creation of an instrumental and methodological basis for forecasting the directions for further developing the international financial architecture in the context of the globalization of the world economy at the national financial systems level. This study concludes that the complex solution of the international financial architecture challenges involves creating the foundations for implementing progressive structural changes in the economy and contributing to sustainable economic development.
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38

John F. Kennedy Space Center. and United States. National Aeronautics and Space Administration. Scientific and Technical Information Program., eds. Statistical short-range guidance for peak wind speed forecasts on Kennedy Space Center/Cape Canaveral Air Force Station: Phase 1 results. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 2002.

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39

John F. Kennedy Space Center. and United States. National Aeronautics and Space Administration. Scientific and Technical Information Program., eds. Statistical short-range guidance for peak wind speed forecasts on Kennedy Space Center/Cape Canaveral Air Force Station: Phase 1 results. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 2002.

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40

Statistical short-range guidance for peak wind speed forecasts on Kennedy Space Center/Cape Canaveral Air Force Station: Phase 1 results. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 2002.

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41

Bechara, Antoine. Impulse Control Disorders in Neurological Settings. Edited by Jon E. Grant and Marc N. Potenza. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780195389715.013.0126.

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This chapter will argue that impulse control disorders, including addiction, are the product of an imbalance between two separate but interacting neural systems: (1) an impulsive amygdala-striatum–dependent neural system that promotes automatic and habitual behaviors and (2) a reflective prefrontal cortex–dependent neural system for decision making, forecasting the future consequences of a behavior, and inhibitory control. The reflective system controls the impulsive system via several mechanisms. However, this control is not absolute; hyperactivity within the impulsive system can override the reflective system. While most prior research has focused on the impulsive system (especially the ventral striatum and its mesolimbic dopamine projection) in promoting the motivation and drive to seek drugs, or on the reflective system (prefrontal cortex) and its mechanisms for decision making and impulse control, more recent evidence suggests that a largely overlooked structure, namely the insula, plays a key role in maintaining poor impulse control, including addiction. This review highlights the potential functional role the insula plays in addiction. We propose that the insula translates bottom-up, interoceptive signals into what subjectively may be experienced as an urge or craving, which in turn potentiates the activity of the impulsive system and/or weakens or hijacks the goal-driven cognitive resources that are needed for the normal operation of the reflective system.
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42

Sobczyk, Eugeniusz Jacek. Uciążliwość eksploatacji złóż węgla kamiennego wynikająca z warunków geologicznych i górniczych. Instytut Gospodarki Surowcami Mineralnymi i Energią PAN, 2022. http://dx.doi.org/10.33223/onermin/0222.

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Hard coal mining is characterised by features that pose numerous challenges to its current operations and cause strategic and operational problems in planning its development. The most important of these include the high capital intensity of mining investment projects and the dynamically changing environment in which the sector operates, while the long-term role of the sector is dependent on factors originating at both national and international level. At the same time, the conditions for coal mining are deteriorating, the resources more readily available in active mines are being exhausted, mining depths are increasing, temperature levels in pits are rising, transport routes for staff and materials are getting longer, effective working time is decreasing, natural hazards are increasing, and seams with an increasing content of waste rock are being mined. The mining industry is currently in a very difficult situation, both in technical (mining) and economic terms. It cannot be ignored, however, that the difficult financial situation of Polish mining companies is largely exacerbated by their high operating costs. The cost of obtaining coal and its price are two key elements that determine the level of efficiency of Polish mines. This situation could be improved by streamlining the planning processes. This would involve striving for production planning that is as predictable as possible and, on the other hand, economically efficient. In this respect, it is helpful to plan the production from operating longwalls with full awareness of the complexity of geological and mining conditions and the resulting economic consequences. The constraints on increasing the efficiency of the mining process are due to the technical potential of the mining process, organisational factors and, above all, geological and mining conditions. The main objective of the monograph is to identify relations between geological and mining parameters and the level of longwall mining costs, and their daily output. In view of the above, it was assumed that it was possible to present the relationship between the costs of longwall mining and the daily coal output from a longwall as a function of onerous geological and mining factors. The monograph presents two models of onerous geological and mining conditions, including natural hazards, deposit (seam) parameters, mining (technical) parameters and environmental factors. The models were used to calculate two onerousness indicators, Wue and WUt, which synthetically define the level of impact of onerous geological and mining conditions on the mining process in relation to: —— operating costs at longwall faces – indicator WUe, —— daily longwall mining output – indicator WUt. In the next research step, the analysis of direct relationships of selected geological and mining factors with longwall costs and the mining output level was conducted. For this purpose, two statistical models were built for the following dependent variables: unit operating cost (Model 1) and daily longwall mining output (Model 2). The models served two additional sub-objectives: interpretation of the influence of independent variables on dependent variables and point forecasting. The models were also used for forecasting purposes. Statistical models were built on the basis of historical production results of selected seven Polish mines. On the basis of variability of geological and mining conditions at 120 longwalls, the influence of individual parameters on longwall mining between 2010 and 2019 was determined. The identified relationships made it possible to formulate numerical forecast of unit production cost and daily longwall mining output in relation to the level of expected onerousness. The projection period was assumed to be 2020–2030. On this basis, an opinion was formulated on the forecast of the expected unit production costs and the output of the 259 longwalls planned to be mined at these mines. A procedure scheme was developed using the following methods: 1) Analytic Hierarchy Process (AHP) – mathematical multi-criteria decision-making method, 2) comparative multivariate analysis, 3) regression analysis, 4) Monte Carlo simulation. The utilitarian purpose of the monograph is to provide the research community with the concept of building models that can be used to solve real decision-making problems during longwall planning in hard coal mines. The layout of the monograph, consisting of an introduction, eight main sections and a conclusion, follows the objectives set out above. Section One presents the methodology used to assess the impact of onerous geological and mining conditions on the mining process. Multi-Criteria Decision Analysis (MCDA) is reviewed and basic definitions used in the following part of the paper are introduced. The section includes a description of AHP which was used in the presented analysis. Individual factors resulting from natural hazards, from the geological structure of the deposit (seam), from limitations caused by technical requirements, from the impact of mining on the environment, which affect the mining process, are described exhaustively in Section Two. Sections Three and Four present the construction of two hierarchical models of geological and mining conditions onerousness: the first in the context of extraction costs and the second in relation to daily longwall mining. The procedure for valuing the importance of their components by a group of experts (pairwise comparison of criteria and sub-criteria on the basis of Saaty’s 9-point comparison scale) is presented. The AHP method is very sensitive to even small changes in the value of the comparison matrix. In order to determine the stability of the valuation of both onerousness models, a sensitivity analysis was carried out, which is described in detail in Section Five. Section Six is devoted to the issue of constructing aggregate indices, WUe and WUt, which synthetically measure the impact of onerous geological and mining conditions on the mining process in individual longwalls and allow for a linear ordering of longwalls according to increasing levels of onerousness. Section Seven opens the research part of the work, which analyses the results of the developed models and indicators in individual mines. A detailed analysis is presented of the assessment of the impact of onerous mining conditions on mining costs in selected seams of the analysed mines, and in the case of the impact of onerous mining on daily longwall mining output, the variability of this process in individual fields (lots) of the mines is characterised. Section Eight presents the regression equations for the dependence of the costs and level of extraction on the aggregated onerousness indicators, WUe and WUt. The regression models f(KJC_N) and f(W) developed in this way are used to forecast the unit mining costs and daily output of the designed longwalls in the context of diversified geological and mining conditions. The use of regression models is of great practical importance. It makes it possible to approximate unit costs and daily output for newly designed longwall workings. The use of this knowledge may significantly improve the quality of planning processes and the effectiveness of the mining process.
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