Texas Instruments 83CML/ILI/U Guidebook - Page 227

Xlistname, Ylistname, freqlist, regequ, iterations, period

Page 227 highlights

PwrReg (axb) Logistic c / (1+aäeLbx) SinReg a sin(bx+c)+d PwrReg (power regression) fits the model equation y=axb to the data using a least-squares fit and transformed values ln(x) and ln(y). It displays values for a and b; when DiagnosticOn is set, it also displays values for r2 and r. PwrReg [Xlistname,Ylistname,freqlist,regequ] Logistic fits the model equation y=c / (1+aäeLbx) to the data using an iterative least-squares fit. It displays values for a, b, and c. Logistic [Xlistname,Ylistname,freqlist,regequ] SinReg (sinusoidal regression) fits the model equation y=a sin(bx+c)+d to the data using an iterative least-squares fit. It displays values for a, b, c, and d. At least four data points are required. At least two data points per cycle are required in order to avoid aliased frequency estimates. SinReg [iterations,Xlistname,Ylistname,period,regequ] iterations is the maximum number of times the algorithm will iterate to find a solution. The value for iterations can be an integer , 1 and  16; if not specified, the default is 3. The algorithm may find a solution before iterations is reached. Typically, larger values for iterations result in longer execution times and better accuracy for SinReg, and vice versa. A period guess is optional. If you do not specify period, the difference between time values in Xlistname must be equal and the time values must be ordered in ascending sequential order. If you specify period, the algorithm may find a solution more quickly, or it may find a solution when it would not have found one if you had omitted a value for period. If you specify period, the differences between time values in Xlistname can be unequal. Note: The output of SinReg is always in radians, regardless of the Radian/Degree mode setting. A SinReg example is shown on the next page. Statistics 12-27

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Statistics
12-27
PwrReg
(power regression) fits the model equation y=ax
b
to
the data using a least-squares fit and transformed values
ln(x) and ln(y). It displays values for
a
and
b
; when
DiagnosticOn
is set, it also displays values for
r
2
and
r
.
PwrReg
[
Xlistname
,
Ylistname
,
freqlist
,
regequ
]
Logistic
fits the model equation y=c / (1+a
ä
e
L
bx
) to the data
using an iterative least-squares fit. It displays values for
a
,
b
,
and
c
.
Logistic
[
Xlistname
,
Ylistname
,
freqlist
,
regequ
]
SinReg
(sinusoidal regression) fits the model equation
y=a sin(bx+c)+d to the data using an iterative least-squares
fit. It displays values for
a
,
b
,
c
, and
d
. At least four data
points are required. At least two data points per cycle are
required in order to avoid aliased frequency estimates.
SinReg
[
iterations
,
Xlistname
,
Ylistname
,
period
,
regequ
]
iterations
is the maximum number of times the algorithm
will iterate to find a solution. The value for
iterations
can
be an integer
1 and
±
16; if not specified, the default is 3.
The algorithm may find a solution before
iterations
is
reached. Typically, larger values for
iterations
result in
longer execution times and better accuracy for
SinReg
, and
vice versa.
A
period
guess is optional. If you do not specify
period
, the
difference between time values in
Xlistname
must be equal
and the time values must be ordered in ascending
sequential order. If you specify
period
, the algorithm may
find a solution more quickly, or it may find a solution when
it would not have found one if you had omitted a value for
period
. If you specify
period
, the differences between time
values in
Xlistname
can be unequal.
Note:
The output of
SinReg
is always in radians, regardless of the
Radian/Degree
mode setting.
A
SinReg
example is shown on the next page.
PwrReg
(ax
b
)
Logistic
c/(1+a
ä
e
L
bx
)
SinReg
a sin(bx+c)+d