Least Squares

Least squares is a common way to measure errors in statistical analysis. The least squares formula is best known for favoring things with a lot of small errors over those with a few large errors.

Least Squares Linear Regression (LIN) FutureSource uses the least squares technique to fit a straight line to the data. In simple terms, the software system computes the linear trend with 1 to time.

Least Squares Method: A technique of fitting a curve close to some given points that minimizes the sum of the squares of the deviations of the given points from the curve. Leg: One side of a spread.

Least Squares Method A statistical method to derive the formula for a line that fits the data points by minimizing the sum of the squares of the deviations of the given points from the line. This method is used in calculating linear regression.

Sum Of Least Squares The Sum Of Least Squares method provides an objective measure for comparing a number of straight lines to find the one that best fits the selected data.

LSMA - Least Squares Moving Average Also called "moving linear regression" or "regression oscillator".

Box-Jenkins Linear Least Squares The additive structure of Box-Jenkins models with a polynomial structure. Box-Jenkins Method From G.E.P. Box and G.M. Jenkins, who authored Time Series Analysis: Forecasting and Control.

The trend is determined by calculating a Linear Regression Trendline using the "least squares fit" method. This method helps to minimum distance between the data points and a Linear Regression Trendline.

TSF, the Time Series Forecast indicator, consists of linear regression measurements using the Least Squares method. Linear regression is a statistical tool for forecasting future Forex market values comparing to past values.

The Time Series Forecast is determined by calculating a linear regression trendline using the "least squares fit" method.

A Linear Regression trend line is simply a trend line drawn between two points using the least squares fit method.  The trend line is displayed in the exact middle of the prices.

To calculate the Time Series Forecast you have to use a "least squares fit" technique to calculate a linear regression trendline, ...

EPS Growth Rate, 3 Year The compound 3-year growth rate calculated using the least squares fit over the latest two to three years' earnings per share on a running 12-month basis. more... EPS Rating (See Earnings Per Share Rating) ...

Endpoint Moving Average - The endpoint moving average uses a least squares (linear regression) fit to derive each point on the moving average line based on the preceding period.

For information on calculating linear regression using the least squares method (the basis behind time series moving averages), refer to any basic statistics book.

A Linear Regression Trendline is a straight line plotted through past prices of a given security via the least squares method. The calculation of this line is described above under Linear Regression.

A Linear Regression Trendline is a straight line drawn through a chart of a security's prices using the least squares method.

It may be estimated using ordinary least squares (OLS) regression analysis. Often an attribute vector (or dummy variable) is assigned to each characteristic or group of characteristics.

For example, an ANN that is used to fit a nonlinear regression curve, using one input, one linear output, and one hidden layer with a logistic transfer function, can function like a polynomial regression or least squares spline.

See also: Square, Regression, Point, Price, Trend