Techniques and Statistical Forecast

ForecastX offers over 25 statistical forecasting techniques and over 50 descriptive metrics and statistics. This ensures that beginning forecasters and advanced statisticians alike can take advantage of the power of ForecastX, no matter what their forecasting challenges may be.

Forecasting Techniques	Accuracy Statistics
Adaptive Exponential Smoothing	AIC
Bass Model	Adjusted R Square
Box Jenkins (ARIMA modeling)	BIC
Brown’s Double Exponential Smoothing	Chi-Square Brown’s
Census II X-11 (Optimize, Multiplicative and Additive)	Cochrane-Orcutt
Croston’s Intermittent Method	Confidence Interval
Decomposition (Additive and Multiplicative)	Error
Event/Promotional Modeling	Mean Absolute Percent Error
Gompertz Curve	Mean Error
Holt’s Double Exponential Smoothing	Mean Absolute Error
Holt-Winters (Optimize, Multiplicative and Additive)	Mean Square Error
Linear Regression	Normality Error
Logistic Curve	R Square
Moving Average	Root Mean Square Error
Multiple Regression	Standard Deviation of Error
New Product Forecasting	Sum of Squared Error
Polynomial Regression with Stepwise Enhancement	Theil’s Statistic
Procast	Weight Mean Absolute Percent Error
Probit Curve
Simple Exponential Smoothing	Distributions
Stepwise Regression w/ Dynamic Lagging	Erlang B
Triple Exponential Smoothing	Erlang C
Weighted Moving Average	Mean Square Deviation
Replenishment Statistics	Median
Confidence Interval	Min
Safety Stock	Mode
Stocking Level (Slow Moving Demand)	Partial Auto Correlation Coefficient
Descriptive Statistics	Poisson
ABC	Range
Auto Correlation	Root Mean Square
Auto Covariance	Skewness
Coefficient of Determination by Pairwise Coefficient of Determination	Standard Deviation
Coefficient of Variance by Coefficient of Variation	Sum of Square Deviation
Covariance	Variance
Correlation Coefficient
Durbin-Watson
Kurtosis
Ljung Box
Max
Mean
Mean Absolute Deviation

For definitions and explanations of the listed forecasting techniques and statistical methods, visit John Galt’s website at www.johngalt.com and go to the education page, then the statistical methods page, or go directly to www.johngalt.com/galt_university/statistical_methods.shtml.