You can include any additonal Statistical methods using Open Source R, Tibco Enterprise Runtime for R,
SAS, Matlab
|
Avg(Arg1, ...) |
ChiDist(Arg1) |
ChiInv(Arg1) |
Count(Arg1) |
CountBig(Arg1) |
Covariance(Arg1, Arg2) |
FDist(Arg1) |
FInv(Arg1) |
First(Arg1) |
GeometricMean() |
IQR(Arg1) |
L95(Arg1) |
Last(Arg1) |
LAV(Arg1) |
LIF(Arg1) |
LOF(Arg1) |
Max(Arg1, ...) |
MeanDeviation(Arg1, ...) |
Median(Arg1) |
MedianAbsoluteDeviation(Arg1, ...) |
Min(Arg1, ...) |
NormDist(Arg1) |
NormInv(Arg1) |
NthLargest(Arg1, Arg2) |
NthSmallest(Arg1, Arg2) |
Outliers(Arg1) |
P10(Arg1) |
P90(Arg1) |
PctOutliers(Arg1) |
Percent(Arg1, Arg2) |
Percentile(Arg1, Arg2) |
Q1(Arg1) |
Q3(Arg1) |
Range(Arg1) |
StdDev(Arg1) |
StdErr(Arg1) |
TDist(Arg1) |
TInv(Arg1) |
TrimmedMean(Arg1, Arg2) |
U95(Arg1) |
UAV(Arg1) |
UIF(Arg1) |
UniqueCount(Arg1) |
UOF(Arg1) |
ValueForMax(Arg1, Arg2) |
ValueForMin(Arg1, Arg2) |
Var(Arg1) |
WeightedAverage(Arg1, Arg2) |
There are also |
Binning functions |
Lot of time users need to write back to a database. Spotfire provides different ways to do this, Without going thru the code I am going to talk thru the different options available. But if you need detailed instructions, please leave some comments and will try to provide one 1) Stored Procedures. Advantages : Complex logic is easy to encapuslate in procedures. Also you are not storing username/passwords anywhere Spotfire can execute stored procedures and these procedures could be fetching data, or can be procedures that can be run Pre or Post running a query. You can then use procedures that basically update your database table or even inserts new rows in tables. When using Spotfire information model it allows you to use these procedures which you can repurpose for updating your database. Spotfire also understands inputs to a procedure and they can be mapped to your marked rows/filtered rows/ properties/constants etc from your analytics. Steps to do that would be ...
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