Input/Output:

 

 

 

Level 1/Argument 1

 

Level 1/Item 1

 

 

 

 

 

 

 

 

 

 

 

z

 

→

 

log z

 

 

 

'symb'

→

'LOG(symb)'

 

 

 

 

 

 

 

See also:

ALOG, EXP, ISOL, LN

 

 

 

 

 

 

 

 

 

 

 

 

LOGFIT

Command

 

 

 

 

Type:

 

 

 

 

Description:

Logarithmic Curve Fit Command: Stores LOGFIT as the fifth parameter in the reserved variable

 

ΣPAR, indicating that subsequent executions of LR are to use the logarithmic curve-fitting model.

 

LINFIT is the default specification in ΣPAR.

 

 

Access:

…µLOGFIT

 

 

 

 

Input/Output: None

 

 

 

 

See also:

BESTFIT, EXPFIT, LINFIT, LR, PWRFIT

 

 

 

 

 

 

 

 

 

 

LQ

Command

 

 

 

 

Type:

 

 

 

 

Description:

LQ Factorization of a Matrix Command: Returns the LQ factorization of an m × n matrix.

 

LQ factors an m × n matrix A into three matrices:

 

 

 

•

L is a lower m × n trapezoidal matrix.

 

 

 

 

•

Q is an n × n orthogonal matrix.

 

 

 

 

 

•

P is a m × m permutation matrix.

 

 

 

 

Where P × A = L × Q.

 

 

 

 

Access:

!Ø FACTORIZATION LQ

 

( Ø is the left-shift of the 5key).

 

!´MATRIX FACTORS LQ

 

( ´is the left-shift of the Pkey).

Input/Output:

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Level 1/Argument 1

 

Level 3/Item 1

Level 2/Item 2

Level 1/Item 3

 

 

 

 

 

 

 

 

 

 

 

[[ matrix ]]A

→

[[ matrix ]]L

[[ matrix ]]Q

[[ matrix ]]P

See also:

LSQ, QR

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

LR

Command

 

 

 

 

Type:

 

 

 

 

Description: Linear Regression Command: Uses the currently selected statistical model to calculate the linear regression coefficients (intercept and slope) for the selected dependent and independent variables in the current statistics matrix (reserved variable ΣDAT).

The columns of independent and dependent data are specified by the first two elements in the reserved variable ΣPAR, set by XCOL and YCOL, respectively. (The default independent and dependent columns are 1 and 2.) The selected statistical model is the fifth element in ΣPAR. LR stores the intercept and slope (untagged) as the third and fourth elements, respectively, in ΣPAR.

The coefficients of the exponential (EXPFIT), logarithmic (LOGFIT), and power (PWRFIT) models are calculated using transformations that allow the data to be fitted by standard linear regression. The equations for these transformations appear in the table below, where b is the intercept and m is the slope. The logarithmic model requires positive x-values (XCOL), the exponential model requires positive y-values (YCOL), and the power model requires positive x- and y-values.

3-138 Full Command and Function Reference