Cycles and Exponential Smoothing Models

Sep 20, 2012

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How Good is Your Forecast?. Can your forecast beat a Moving Average?Business forecasters use Moving Average as a point of comparisonMAPE for MA modelMAPE for your modelExample of two Data SeriesX with a Moving Average MAPE of 23%Your model's MAPE of 15%Y with a Moving Average MAPE of 12%Your

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Cycles and Exponential Smoothing Models

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1. Cycles and Exponential Smoothing Models Materials for this lecture Lecture 4 Cycles.XLS Lecture 4 Exponential Smoothing.XLS Read Chapter 15 pages 18-30 Read Chapter 16 Section 14

Adjusted Exponential Smoothing

Adjusted Exponential Smoothing. Paul Mendenhall BusM 361 Professor Foster. Outline. Tool defined Equation Explained Illustrated step by step problem Practice Problem Summary. Definition. Times Series Forecasting model Adjusts for trends in information. Trends. What are trends?

1.44k views • 22 slides

MOVING AVERAGES AND EXPONENTIAL SMOOTHING

MOVING AVERAGES AND EXPONENTIAL SMOOTHING. Farideh Dehkordi-Vakil. Introduction. This chapter introduces models applicable to time series data with seasonal, trend, or both seasonal and trend component and stationary data. Forecasting methods discussed in this chapter can be classified as:

1.31k views • 48 slides

Exponential models

Exponential models. Standard form(s) of an exponential. y = a b x a is the initial value (y-intercept) b is the growth factor y = a e r x a is the initial value (y-intercept) r is the “per-capita rate” also called “exponential growth rate” Conversion b = e r , r= ln (b).

140 views • 0 slides

Exponential Smoothing

Exponential Smoothing . Using Solver to optimize the value of alpha. Using Solver to Optimize Alpha. Using Solver to Optimize Alpha. Using Solver to Optimize Alpha. Using Solver to Optimize Alpha. Using Solver to Optimize Alpha.

163 views • 6 slides

Exponential Models

Exponential Models. Thursday, April 24 th. Derivative Rules Warm Up. To make sure that no one is wobbly on derivative rules, we have a page of practice. Half-life. 6mg of a radioactive isotope of gold, Au-198, decays into 4.6mg after 1day. What is the decay constant for Au-198?

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Exponential Smoothing

Exponential Smoothing. Part 2 – Holt’s Local Linear Trend Through Part 4 – Damped Trend. Holt’s Local Linear Trend. Holt (1957) extended SES to allow forecasting of data with trends. Two smoothing parameters: α and β * with values between 0 and 1. Simple Exponential Smoothing.

363 views • 11 slides

Exponential Smoothing

Exponential Smoothing. Part 1 – Simple SES. Simple Exponential Smoothing (SES). Simple Exponential Smoothing.

339 views • 16 slides

Exponential Smoothing

Exponential Smoothing. Information Flows and Equations. Simple Exponential Smoothing. Simple Exponential Smoothing. Holt’s Method Exponential Smoothing. Holt’s Method Exponential Smoothing. Holt-Winters Exponential Smoothing. Holt-Winters Exponential Smoothing.

226 views • 7 slides

Cycles and Exponential Smoothing Models

Cycles and Exponential Smoothing Models. Materials for this lecture Lecture 4 Cycles.XLS Lecture 4 Exponential Smoothing.XLS Read Chapter 15 pages 18-30 Read Chapter 16 Section 14. How Good is Your Forecast?. Can your forecast beat a Moving Average?

351 views • 22 slides

Cycles and Exponential Smoothing Models

Cycles and Exponential Smoothing Models. Materials for this lecture Lecture 4 Cycles.XLS Lecture 4 Exponential Smoothing.XLSX Read Chapter 15 pages 18-30 Read Chapter 16 Section 14. How Good is Your Forecast?. Can your forecast beat a Moving Average?

364 views • 22 slides

Exponential Smoothing Methods

Exponential Smoothing Methods. Chapter Topics. Introduction to exponential smoothing Simple Exponential Smoothing Holt’s Trend Corrected Exponential Smoothing Holt-Winters Methods Multiplicative Holt-Winters method Additive Holt-Winters method. Motivation of Exponential Smoothing.

2.63k views • 74 slides

Exponential Smoothing

Exponential Smoothing. Last period’s forecast ( F t ) Last periods actual value ( A t ) Select value of smoothing coefficient, ,between 0 and 1.0 Forecast quality is highly dependent on selection of alpha: High alpha values generate forecasts that respond quickly to recent data

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Section 7.2: Exponential Smoothing

Section 7.2: Exponential Smoothing. Quantitative Decision Making 7 th ed By Lapin and Whisler. Simple Exponential Smoothing. Graphing Actual vs Forecast Values. Forecasting Errors. Two Parameter Smoothing. Simple Exponential Smoothing. Compute T 3. Compute b 3.

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4 – Exponential Smoothing Methods

4 – Exponential Smoothing Methods. Signal and Noise. Smoothing can be seen as a technique to separate the signal and the noise as much as possible and in that a smoother acts as a filter to obtain an "estimate" for the signal. Smoothing a data set. Smoothing a Constant Process.

1.51k views • 83 slides

Adjusted Exponential Smoothing

Adjusted Exponential Smoothing. AF t +1 = F t +1 + T t +1 where T = an exponentially smoothed trend factor T t +1 =  ( F t +1 - F t ) + (1 -  ) T t where T t = the last period trend factor  = a smoothing constant for trend. Adjusted Exponential Smoothing Example.

1.56k views • 54 slides

Forecasting Exponential Smoothing For Stationary Models

Forecasting Exponential Smoothing For Stationary Models. Exponential Smoothing. The Last Period method uses only one period (the last) and the n-Period Moving Average and Weighted Moving methods use only the last n periods to make forecasts – the rest of the data is ignored .

552 views • 14 slides

MOVING AVERAGES AND EXPONENTIAL SMOOTHING

MOVING AVERAGES AND EXPONENTIAL SMOOTHING. Dr. Mohammed Alahmed http://fac.ksu.edu.sa/alahmed alahmed@ksu.edu.sa (011) 4674108. Introduction. This chapter introduces models applicable to time series data with seasonal, trend, or both seasonal and trend component and stationary data.

701 views • 58 slides

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