Texas Instruments Voyage 200 User Manual page 943

Uses the least-squares algorithm and transformed
LnReg
values ln(x) and y to fit the model equation:
y=a+b ln(x)
Uses the least-squares algorithm to fit the model
Logistic
equation:
y=a/(1+b *
Uses the median-median line (resistant line)
MedMed
technique to calculate summary points x1, y1, x2,
y2, x3, and y3, and fits the model equation:
y=ax+b
where a is the slope and b is the y-intercept.
Uses the least-squares algorithm and transformed
PowerReg
values ln(x) and ln(y) to fit the model equation:
y=ax
Uses the least-squares algorithm to fit the second-
QuadReg
order polynomial:
y=ax 2 +bx+c
For three data points, the equation is a polynomial
fit; for four or more, it is a polynomial regression.
At least three data points are required.
Uses the least-squares algorithm to fit the fourth-
QuartReg
order polynomial:
y=ax 4 +bx 3 +cx 2 +dx+e
For five data points, the equation is a polynomial
fit; for six or more, it is a polynomial regression. At
least five data points are required.
Uses the least-squares algorithm to fit the model
SinReg
equation:
y=a sin(bx+c)+d
Appendix B: Technical Reference
e
^(c * x))+d
b
937