Natsuki Nakagawa Posted February 4, 2020 Share Posted February 4, 2020 I can display the normal distribution from the properties of the histogram, but I don't know how to display the lognormal distribution. Does anyone has idea on how to do this Link to comment Share on other sites More sharing options...
Khushboo Rabadia Posted March 12, 2020 Share Posted March 12, 2020 You can take a look at below wiki articles: https://community.spotfire.com/wiki/simple-probability-plot-template-tibco-spotfirer https://community.spotfire.com/modules/simple-probability-plot-analysis-template-tibco-spotfire Link to comment Share on other sites More sharing options...
Hector Martinez 2 Posted April 15, 2020 Share Posted April 15, 2020 Creating a Log-Normal Distribution plot in Spotfire isvery do-able, just not "out-of-the-box"; it requires configuration and the use of a simple data function (see below). Spotfire has an 'auto-bin' function that allow the creation of a Distribution of Normal Data; but that data is in linear scale. When the data is in log scale, the current (Spotfire v10.8) 'auto-bin' does not know how to return the correct "bins" for data that is log-scale and therefore displays the expected distribution (brar chart) incorrectly. I order to correct for this you have to send the data to a TERR data function (script below) that will return the correct log distributed bins into a property. This property can be used in the bar charts' x-axis' expression in conjunction with the BinBySpecificLimits(). Here is an example where the column [myData] is Real() and is lognormally distributed. The property '${analyzeLogBins}' holds the returning string value from the TERR data function. my example (attached image): y-axis: count()x-axis: BinBySpecificLimits([myData],${analyzeLogBins}) as [Gross Amt] TERR data function: # Parameters: # X - input; column of data # Y - output; string value if(length(X)>0){ lb = log10(min(X)) if (is.na(lb) | (min(X)==0)) { lb = 0.00000001 } else{ lb = log10(min(X)) } myout = exp(log(10)*seq(lb,log10(max(X)),length.out = userBins)) Y = toString(round(myout,digits=2)) }else{ Y='0' } Hope this helps you in creating your log-normal distribution plot. :) Link to comment Share on other sites More sharing options...
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