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regressions.rpn sums up the expressions x, x**2, y, y**2, x y, 1, ln x, (ln x)**2, y ln x, ln y, (ln y)**2, x lny, lnx lny. If any of the logarithmic models can't be supported due to negative values, then it will be disabled (correlation returns zero in this case). The user can also manually disable the logarithmic models.
[+]  Sum up the expressions needed for the regression calculations. Returns the new n. 
[]  Subtract expressions.
This lets you correct entries made with [+] .
Returns the new n. 
clr  Clear sums. 
sum  Calculate sums. Returns sum(x), sum(y) 
mean  Calculate mean values. Returns mean(x), mean(y) 
wm  Calculate the weighted mean. Returns wmean(x) where the y_{i} are the weights. 
sdev  Calculate standard deviations. Returns sdev(x), sdev(y). Requires at least two sets of values. 
Model  Regression model chose dialog:
best lin log exp pwr .
best calculates all possible regression models and choses
the one with the highest correlationsquare.
Returns the index of the chosen model. 
x  Calculate x_{f} (forecast) from y. 
y  Calculate y_{f} (forecast) from x. 
a  Slope parameter. Zero if the chosen model is illegal (because of negative values). 
b  Offset parameter. 
r  Correlation. Between 1 and 1. Values far from zero are better. 
To calculate statistics and regressions on the following data sets, enter:

clr
11 Enter 2 [+] 13 Enter 3 [+] 17 Enter 5 [+] 19 Enter 7 [+] 
Statistics results:
function  tab  result(s) 
sum  sum  17.0000 60.0000 
mean  mean  4.2500 15.0000 
weighted mean  wm  4.6500 
standard deviation  sdev  2.2174 3.6515 
Regressions results:
model  a  b  r  y_{f}(11)  x_{f}(23) 
lin  1.6271  8.0847  0.9881  25.9831  9.1667 
log  6.5833  6.1996  0.9964  21.9856  12.8325 
exp  0.1099  9.1903  0.9781  30.7775  8.3489 
pwr (best)  0.4494  8.0395  0.9972  23.6178  10.3699 
The regression parameters a and b are optimized for least
squares.
The two partial differentials produce a system of equations from which
a and b can be calculated.
The correlation can be calculated from variances and covariance. See any good math textbook for more information. 
source:
regressions.rpn
source stripped of comments and blanks, to fit into Palm's clipboard:
regressionss.rpn
best
model is chosen.
This is not a bug since with two value pairs, all four models achieve
the same correlation 1.
Please send your bug reports, if you have any.
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