Multivariate nonlinear regression analysis DRS

eaihua

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Soft name: DRS

Soft Ver: 2008

Soft language: Engish

Run environment: Win9x/NT/2000/XP

Soft size: 1950 KB

Soft presentation: Least Cubic Method is a new method for data regression analyse , it expanded Least Square Method, According to the principle, this program can be used to work out single factor linear data regression, multi factors linear data regression, single factor non-linear data regression, and multifactors non-linear data regression.

Soft download1: DRS - Reviews and free DRS downloads at Download.com

Soft download2:

chart of multivariate nonlinear




Purchase contact: [email][email protected][/email]
Purchase web: [url=http://www.eaihua.com]°®»ª¼ÆËã»ú¹¤×÷ÊÒ
 
Can you explain to me how I might use this software to make myself rich beyond my wildest dreams?
 
Explain for Multivariate nonlinear regression analysis DRS

The first and second chart is the regression three-dimensional data model made surface chart.

The third chart is the regression of four-dimensional data model made by the three-dimensional surface chart at the fourth dimension data change the change.
 
Explain for Multivariate nonlinear regression analysis DRS

The first and second chart is the regression three-dimensional data model made surface chart.

The third chart is the regression of four-dimensional data model made by the three-dimensional surface chart at the fourth dimension data change the change.
 
Hello Mr. Wong.
Congratulations on your software. Could your software import a typical trading data (in this case: symbol, intraday, date, time, Open, High, Low, Close, Volume) and plot the the least cubic regression analysis? The only important data series would probably be the time as X2, Close as Y, and Volume as X1.

I am sure it could be interesting if you can post the result with the sample series below. I noticed your plots are in monochrome (one color). Do you have plans to expand that to multicolor gradients?

How fast is the software and could it plot this in realtime? perhaps every minute or less with a dataseries in the hundreds (500 for example).

Cheers.

Code:
ES0308,I,20080305,11:50,1338,1338.75,1335.25,1336,18390
ES0308,I,20080305,11:55,1335.75,1338.25,1335.75,1337.25,14594
ES0308,I,20080305,12:00,1337.5,1338.75,1337.25,1337.75,8590
ES0308,I,20080305,12:05,1338,1345,1337.75,1342.5,82005
ES0308,I,20080305,12:10,1342.5,1344.25,1337.75,1339.25,57116
ES0308,I,20080305,12:15,1339.25,1342.75,1338.5,1340,42622
ES0308,I,20080305,12:20,1340,1341,1336.25,1338.25,37599
ES0308,I,20080305,12:25,1338.25,1339.5,1337.25,1339.25,12527
ES0308,I,20080305,12:30,1339.5,1339.5,1333.25,1335.25,53472
ES0308,I,20080305,12:35,1335.25,1337.25,1334.25,1336.25,28364
ES0308,I,20080305,12:40,1336,1336.75,1332.25,1333.75,33355
ES0308,I,20080305,12:45,1334,1336.75,1333.25,1335.25,16090
ES0308,I,20080305,12:50,1335.5,1336.5,1334,1334.75,11304
ES0308,I,20080305,12:55,1334.5,1335.75,1333,1335.75,14796
ES0308,I,20080305,13:00,1335.5,1336.5,1334,1335.75,11647
ES0308,I,20080305,13:05,1336,1337.75,1335.25,1335.75,16587
ES0308,I,20080305,13:10,1336,1338.5,1335.5,1338.5,7784
ES0308,I,20080305,13:15,1338.5,1338.5,1334.5,1335.25,22519
ES0308,I,20080305,13:20,1335.5,1337,1329.5,1330.25,46560
ES0308,I,20080305,13:25,1330.25,1330.75,1326.75,1327.25,50839
ES0308,I,20080305,13:30,1327.25,1329.75,1327,1328.25,35593
ES0308,I,20080305,13:35,1328.25,1328.75,1326,1326.25,51876
ES0308,I,20080305,13:40,1326,1326.25,1320.5,1322.5,96118
ES0308,I,20080305,13:45,1322.75,1324.25,1320.25,1323.75,45510
ES0308,I,20080305,13:50,1324,1325,1322.5,1323.5,29684
ES0308,I,20080305,13:55,1323.25,1324.25,1322.75,1322.75,13118
ES0308,I,20080305,14:00,1322.75,1326,1322,1324.5,26375
ES0308,I,20080305,14:05,1324.75,1326.75,1321.5,1325.25,30765
ES0308,I,20080305,14:10,1325,1326.25,1323.75,1326,17116
ES0308,I,20080305,14:15,1326,1327.5,1324.75,1327.5,23186
ES0308,I,20080305,14:20,1327.5,1329,1327.25,1328,28776
ES0308,I,20080305,14:25,1328,1328.25,1326.25,1327.5,14508
ES0308,I,20080305,14:30,1327.5,1329.75,1327,1328,23116
ES0308,I,20080305,14:35,1328,1328.25,1326.25,1326.75,12335
ES0308,I,20080305,14:40,1326.75,1329,1326.5,1327.75,15734
ES0308,I,20080305,14:45,1327.75,1329.25,1327,1328,14394
ES0308,I,20080305,14:50,1328,1331.75,1328,1330.75,31281
ES0308,I,20080305,14:55,1331,1333.5,1330,1331.25,27891
 
You data and request to do chart of Regression model

Hello Mr.thrunner

Time as X2, Close as Y, and Volume as X1.

:clap:
21.gif

22.gif

(y)
 
Last edited:
These look like nets to catch the sprats. The KISS method is non-existent here.

Smacks of desperation, to me.
 
I believe that one day, many person will understand and accept, We can face-to-face xchanges, with No problem.
 
Eaihua,

Can this be applied to all instruments - bonds, fx, equities, etc?

Can Excel data be imported into the programme?

Thank you.

Grant.
 
Eaihua,

Can this be applied to all instruments - bonds, fx, equities, etc?

Can Excel data be imported into the programme?

Thank you.

Grant.

Grant,
Heaven knows how or why, but you always seem to be a highly intelligent chap :cheesy:
Can you please explain for a poor dumb radge like me, in words of 3 syllables or less, WTF this is all about ? cheers mate
 
Grant,
Heaven knows how or why, but you always seem to be a highly intelligent chap :cheesy:
Can you please explain for a poor dumb radge like me, in words of 3 syllables or less, WTF this is all about ? cheers mate

and preferably is words of 1 syllable for me?:)

UTB
 
Eaihua,

Can this be applied to all instruments - bonds, fx, equities, etc?

Can Excel data be imported into the programme?

Thank you.

Grant.
Grant, I think I can see where you think you’re headed, but save yourself some heartache.

Although this may well be a very polished product, statistical analysis of multivariate multiple nonlinear regression models with correlated errors uses Finite Fourier Transforms, which as we know, from a financial markets perspective, has issues with data stationarity. Consistency and asymptotic normality of the weighted least squares estimates need to be established under various conditions on the regressor variables which is not possible for the data series you’re thinking of shoving through it. These conditions involve different types of scalings, and the scaling factors are explicit for each types of sets of nonlinear regression models. Basically, even if you didn’t have the issues I mention above with data stationarity, you’d need to rewrite the software for each set of data for each instrument for each change (new) last period.

Of course, I may have got it wrong.
 
Grant, I think I can see where you think you’re headed, but save yourself some heartache.

Although this may well be a very polished product, statistical analysis of multivariate multiple nonlinear regression models with correlated errors uses Finite Fourier Transforms, which as we know, from a financial markets perspective, has issues with data stationarity. Consistency and asymptotic normality of the weighted least squares estimates need to be established under various conditions on the regressor variables which is not possible for the data series you’re thinking of shoving through it. These conditions involve different types of scalings, and the scaling factors are explicit for each types of sets of nonlinear regression models. Basically, even if you didn’t have the issues I mention above with data stationarity, you’d need to rewrite the software for each set of data for each instrument for each change (new) last period.

Of course, I may have got it wrong.

i thought English was the standard, accepted language on these Boards ?
 
RC, Blades,

I could explain quite simply, but you would only be confused. Don’t worry about, just leave it to me.

Don Bramble,

That’s exactly what I thought. I was just trying to catch the guy out.

“Âksâr chhôr reăhmŭkh yŭkôleăkpĭntŭ musĕkâtônd sanhyoŭk sannha”. There’s an error in the syntax here (not going to tell you where).

RC,

“I thought English was the standard”. Doesn’t matter to us intellectuals – any will do, won’t they Don? (He’s miles away.)

Grant.
 
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