Forecasting
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Forecasting
Forecasting is the process of making predictions based on past and present data. Later these can be compared (resolved) against what happens. For example, a company might estimate their revenue in the next year, then compare it against the actual results. Prediction is a similar but more general term. Forecasting might refer to specific formal statistical methods employing time series, cross-sectional or longitudinal data, or alternatively to less formal judgmental methods or the process of prediction and resolution itself. Usage can vary between areas of application: for example, in hydrology the terms "forecast" and "forecasting" are sometimes reserved for estimates of values at certain specific future times, while the term "prediction" is used for more general estimates, such as the number of times floods will occur over a long period. Risk and uncertainty are central to forecasting and prediction; it is generally considered a good practice to indicate the degree of uncertainty ...
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Technology Forecasting
Technology forecasting attempts to predict the future characteristics of useful technological machines, procedures or techniques. Researchers create technology forecasts based on past experience and current technological developments. Like other forecasts, technology forecasting can be helpful for both public and private organizations to make smart decisions. By analyzing future opportunities and threats, the forecaster can improve decisions in order to achieve maximum benefits. Today, most countries are experiencing huge social and economic changes, which heavily rely on technology development. By analyzing these changes, government and economic institutions could make plans for future developments. However, not all of historical data can be used for technology forecasting, forecasters also need to adopt advanced technology and quantitative modeling from experts’ researches and conclusions. History Technology forecasting has existed more than a century, but it developed to an e ...
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Energy Forecasting
Energy forecasting includes forecasting demand ( load) and price of electricity, fossil fuels (natural gas, oil, coal) and renewable energy sources (RES; hydro, wind, solar). Forecasting can be both expected price value and probabilistic forecasting. Background When electricity sectors were regulated, utility monopolies used short-term load forecasts to ensure the reliability of supply and long-term demand forecasts as the basis for planning and investing in new capacity. However, since the early 1990s, the process of deregulation and the introduction of competitive electricity markets have been reshaping the landscape of the traditionally monopolistic and government-controlled power sectors. In many countries worldwide, electricity is now traded under market rules using spot and derivative contracts. At the corporate level, electricity load and price forecasts have become a fundamental input to energy companies’ decision making mechanisms. The costs of over- or undercontract ...
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Earthquake Prediction
Earthquake prediction is a branch of the science of seismology concerned with the specification of the time, location, and magnitude of future earthquakes within stated limits, and particularly "the determination of parameters for the ''next'' strong earthquake to occur in a region". Earthquake prediction is sometimes distinguished from '' earthquake forecasting'', which can be defined as the probabilistic assessment of ''general'' earthquake hazard, including the frequency and magnitude of damaging earthquakes in a given area over years or decades. Not all scientists distinguish "prediction" and "forecast", but the distinction is useful. Prediction can be further distinguished from earthquake warning systems, which upon detection of an earthquake, provide a real-time warning of seconds to neighboring regions that might be affected. In the 1970s, scientists were optimistic that a practical method for predicting earthquakes would soon be found, but by the 1990s continuing failure ...
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Economic Forecasting
Economic forecasting is the process of making predictions about the economy. Forecasts can be carried out at a high level of aggregation—for example for GDP, inflation, unemployment or the fiscal deficit—or at a more disaggregated level, for specific sectors of the economy or even specific firms. Economic forecasting is a measure to find out the future prosperity of a pattern of investment and is the key activity in economic analysis. Many institutions engage in economic forecasting: national governments, banks and central banks, consultants and private sector entities such as think-tanks, companies and international organizations such as the International Monetary Fund, World Bank and the OECD. A broad range of forecasts are collected and compiled b"Consensus Economics" Some forecasts are produced annually, but many are updated more frequently. The economist typically considers risks (i.e., events or conditions that can cause the result to vary from their initial estimates). ...
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Time Series
In mathematics, a time series is a series of data points indexed (or listed or graphed) in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time. Thus it is a sequence of discrete-time data. Examples of time series are heights of ocean tides, counts of sunspots, and the daily closing value of the Dow Jones Industrial Average. A time series is very frequently plotted via a run chart (which is a temporal line chart). Time series are used in statistics, signal processing, pattern recognition, econometrics, mathematical finance, weather forecasting, earthquake prediction, electroencephalography, control engineering, astronomy, communications engineering, and largely in any domain of applied science and engineering which involves temporal measurements. Time series ''analysis'' comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series ''forecasting' ...
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Political Forecasting
Political forecasting aims at forecasting the outcomes of political events. Political events can be a number of events such as diplomatic decisions, actions by political leaders and other areas relating to politicians and political institutions. The area of political forecasting concerning elections is highly popular, especially amongst mass market audiences. Political forecasting methodology makes frequent use of mathematics, statistics and data science. Political forecasting as it pertains to elections is related to psephology. History of Election Forecasting People have long been interested in predicting election outcomes. Quotes of betting odds on Pope, papal succession appear as early as 1503, when such wagering was already considered "an old practice." Political betting also has a long history in Great Britain. As one prominent example, Charles James Fox, the late-eighteenth-century Whig statesman, was known as an inveterate gambler. His biographer, George Otto Trevelyan, n ...
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Future
The future is the time after the past and present. Its arrival is considered inevitable due to the existence of time and the laws of physics. Due to the apparent nature of reality and the unavoidability of the future, everything that currently exists and will exist can be categorized as either permanent, meaning that it will exist forever, or temporary, meaning that it will end. In the Occidental view, which uses a linear conception of time, the future is the portion of the projected timeline that is anticipated to occur. In special relativity, the future is considered absolute future, or the future light cone. In the philosophy of time, presentism is the belief that only the present exists and the future and the past are unreal. Religions consider the future when they address issues such as karma, life after death, and eschatologies that study what the end of time and the end of the world will be. Religious figures such as prophets and diviners have claimed to see into t ...
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Sales Forecasting
Sales operations is a set of business activities and processes that help a sales organization run effectively, efficiently and in support of business strategies and objectives. Sales operations may also be referred to as sales, sales support, or business operations. Categories The set of sales operations activities vary from company to company but often include these five categories:< Sales force enablement * Sales process development * Sales process adoption and compliance * Sales development * Sales training * Sales force communications management Business analytics * Sales metrics * Sales forecasting Sales administration * Proposal/contract development * Vendor selection and management * Planning process stewardship Attainment planning * Incentive sales compensation plan design * GTM strategy alignment with roles and components * Territory analysis and definition * Goal setting Sales operations mandate and design * Chief of staff to the sales organization * Stewardship ...
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PECOTA
PECOTA, an acronym for ''Player Empirical Comparison and Optimization Test Algorithm'', is a sabermetric system for forecasting Major League Baseball player performance. The word is a backronym based on the name of journeyman major league player Bill Pecota, who, with a lifetime batting average of .249, is perhaps representative of the typical PECOTA entry. PECOTA was developed by Nate Silver in 2002–2003 and introduced to the public in the book ''Baseball Prospectus 2003''. Baseball Prospectus (BP) has owned PECOTA since 2003; Silver managed PECOTA from 2003 to 2009. Beginning in Spring 2009, BP assumed responsibility for producing the annual forecasts, making 2010 the first baseball season for which Silver played no role in producing PECOTA projections.Nate Silver and Kevin Goldstein, "State of the Prospectus: Spring 2009,BaseballProspectus.com, March 24, 2009. One of several widely publicized statistical systems of forecasts of player performance, PECOTA player forecasts are mar ...
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Customer Demand Planning
Customer demand planning (CDP) is a business-planning process that enables sales teams to develop demand forecasts as input to service-planning processes, production, inventory planning and revenue planning. Definition CDP is an aspect of managing value chains. Generally, the first step of CDP is to forecast product demand. A manager can plan resource deployment in accordance with the resulting forecasts. It's a bottom-up approach vs. top down planning. Associated risks with this method are: Low forecast accuracy and numbers of planners required. There are various software systems that are designed to forecast demand and plan operations. To test the added value of implementing bottom-up approach, applications are providing simulations functionalities to estimate the resulting demand forecast accuracy (e.g. POS sales ; sales invoices ; shipments, etc.) In the manufacturer to retailer model, customer collaborative partnerships have become more common since the 1990s. Although t ...
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Prediction
A prediction (Latin ''præ-'', "before," and ''dicere'', "to say"), or forecast, is a statement about a future event or data. They are often, but not always, based upon experience or knowledge. There is no universal agreement about the exact difference from "estimation"; different authors and disciplines ascribe different connotations. Future events are necessarily uncertain, so guaranteed accurate information about the future is impossible. Prediction can be useful to assist in making plans about possible developments. Opinion In a non-statistical sense, the term "prediction" is often used to refer to an informed guess or opinion. A prediction of this kind might be informed by a predicting person's abductive reasoning, inductive reasoning, deductive reasoning, and experience; and may be useful—if the predicting person is a knowledgeable person in the field. The Delphi method is a technique for eliciting such expert-judgement-based predictions in a controlled way. Th ...
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Land Use Forecasting
Land-use forecasting undertakes to project the distribution and intensity of trip generation, trip generating activities in the metropolitan area, urban area. In practice, land-use models are demand-driven, using as inputs the aggregate information on growth produced by an aggregate economic forecasting activity. Land-use estimates are inputs to the transportation planning process. The discussion of land-use forecasting to follow begins with a review of the Chicago Area Transportation Study (CATS) effort. CATS researchers did interesting work, but did not produce a transferable forecasting model, and researchers elsewhere worked to develop models. After reviewing the CATS work, the discussion will turn to the first model to be widely known and emulated: the Lowry model developed by Ira S. Lowry when he was working for the Pittsburgh Regional Economic Study. Second and third generation Lowry models are now available and widely used, as well as interesting features incorporated ...
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