Bayesian information criterion - Revision history

en>TheSeven: /* References */ include Findley (1991)

2015-01-12T13:39:58Z

References: include Findley (1991)

← Older revision		Revision as of 15:39, 12 January 2015
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	~~Greetings. The author~~'~~s title is Phebe~~ and ~~she feels comfy~~ when ~~people~~ use the full name. ~~North Dakota~~ is ~~where me and~~ my ~~spouse reside~~. ~~Since she was 18 she's been working as a receptionist but her promotion never arrives~~. ~~His wife doesn't like it~~ the ~~way he does~~ but ~~what~~ he ~~really likes doing~~ is to ~~do aerobics and he's been performing~~ it ~~for quite a while~~.<br><br>~~My webpage~~ :: [http://~~nuvem~~.tk/~~altergalactica~~/~~NumbersdbEstepvu nuvem.tk~~]		Myrtle Benny is how I'm known as and I feel comfortable when individuals use the full name. Bookkeeping is my profession. Years in the past we moved to North Dakota. One of the extremely best issues in the globe for him is to gather badges but he is struggling to discover time for it.<br><br>Here is my website :: home std test ([http://203.250.78.160/zbxe/?document_srl=817810&mid=gallery redirected here])

en>طاها: Undid revision 596405815 by طاها (talk)

2014-02-25T22:57:47Z

Undid revision 596405815 by طاها (talk)

← Older revision		Revision as of 00:57, 26 February 2014
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	In [[statistics\|statistical data analysis]] the '''total sum of squares''' (TSS or SST) is a quantity that appears as part of a standard way of presenting results of such analyses. It is defined as being the sum, over all observations, of the squared differences of each observation from the overall [[mean]].<ref>Everitt, B.S. ~~(2002) ''~~The ~~Cambridge Dictionary of Statistics~~'~~', CUP, ISBN 0-521-81099-X</ref>~~		Greetings. The author's title is Phebe and she feels comfy when people use the full name. North Dakota is where me and my spouse reside. Since she was 18 she's been working as a receptionist but her promotion never arrives. His wife doesn't like it the way he does but what he really likes doing is to do aerobics and he's been performing it for quite a while.<br><br>My webpage :: [http://nuvem.tk/altergalactica/NumbersdbEstepvu nuvem.tk]

	~~In [[statistics\|statistical]] [[linear model]]~~s~~, (particularly in standard [[regression model]]s), the '''TSS'''~~ is ~~the [[sum]] of the [[square (algebra)\|square]]s of the difference of the dependent variable~~ and ~~its [[mean]]:~~

	~~:<math>\sum_{i=1}^{n}\left(y_{i}-\bar{y}\right)^2</math>~~

	~~where <math>\bar{y}</math> is~~ the ~~mean~~.

	~~For wide classes of linear models, the total sum of squares equals the [[explained sum of squares]] plus the [[residual sum of squares]]~~. ~~For~~ a ~~proof of this in the multivariate OLS case, see [[Explained sum of squares#Partitioning in the general OLS model\|partitioning in the general OLS model]]~~.

	~~In [[analysis of variance]] (ANOVA)~~ the ~~total sum of squares~~ is ~~the sum of the so-called "within-samples" sum of squares~~ and ~~"between-samples" sum of squares, i~~.~~e., partitioning of the sum of squares.~~
	~~In [[multivariate analysis of variance]] (MANOVA) the following equation applies~~<~~ref name="MardiaK1979Multivariate"~~>~~{{Cite book~~
	~~\| author = [[K. V. Mardia]], J. T. Kent and J. M. Bibby~~
	~~\| title = Multivariate Analysis~~
	~~\| publisher = [[Academic Press]]~~
	~~\| year = 1979~~
	~~\| isbn = 0-12-471252-5~~
	~~}} Especially chapters 11 and 12.~~<~~/ref~~>
	:~~<math>\mathbf{T} = \mathbf{W} + \mathbf{B},<~~/~~math>~~
	~~where '''T''' is the total sum of squares and products (SSP) [[Matrix (mathematics)\|matrix]], '''W''' is the within-samples SSP matrix and '''B''' is the between-samples SSP matrix~~.
	~~Similar terminology may also be used in [[linear discriminant analysis]], where '''W''' and '''B''' are respectively referred to as the within-groups and between-groups SSP matrics~~.~~<ref name="MardiaK1979Multivariate"/>~~

	~~==See also==~~
	*[[Sum of squares (statistics)]]
	*[[Lack-of-fit sum of squares]]

	~~==References==~~
	~~{{Reflist}}~~

	~~[[Category:Regression analysis]]~~
	~~[[Category:Least squares]~~]

129.6.121.164: update ref format to full citation

2014-01-07T17:54:32Z

update ref format to full citation

← Older revision		Revision as of 19:54, 7 January 2014
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	~~Irwin Butts~~ is ~~what my spouse loves to call me although I don't really like becoming known~~ as ~~like that~~. ~~To collect badges~~ is ~~what her family members~~ and ~~her appreciate~~. ~~South Dakota~~ is ~~where me~~ and ~~my husband live~~. ~~He utilized to be unemployed but now he is a computer operator but his marketing never comes~~.<br><br>~~Also visit my homepage - home std test kit~~ ([~~http://payiz~~.~~az/index~~.~~php?do~~=/~~profile~~-~~14379/info/ sneak a peek at these guys~~])		In [[statistics\|statistical data analysis]] the '''total sum of squares''' (TSS or SST) is a quantity that appears as part of a standard way of presenting results of such analyses. It is defined as being the sum, over all observations, of the squared differences of each observation from the overall [[mean]].<ref>Everitt, B.S. (2002) ''The Cambridge Dictionary of Statistics'', CUP, ISBN 0-521-81099-X</ref>

			In [[statistics\|statistical]] [[linear model]]s, (particularly in standard [[regression model]]s), the '''TSS''' is the [[sum]] of the [[square (algebra)\|square]]s of the difference of the dependent variable and its [[mean]]:

			:<math>\sum_{i=1}^{n}\left(y_{i}-\bar{y}\right)^2</math>

			where <math>\bar{y}</math> is the mean.

			For wide classes of linear models, the total sum of squares equals the [[explained sum of squares]] plus the [[residual sum of squares]]. For a proof of this in the multivariate OLS case, see [[Explained sum of squares#Partitioning in the general OLS model\|partitioning in the general OLS model]].

			In [[analysis of variance]] (ANOVA) the total sum of squares is the sum of the so-called "within-samples" sum of squares and "between-samples" sum of squares, i.e., partitioning of the sum of squares.
			In [[multivariate analysis of variance]] (MANOVA) the following equation applies<ref name="MardiaK1979Multivariate">{{Cite book
			\| author = [[K. V. Mardia]], J. T. Kent and J. M. Bibby
			\| title = Multivariate Analysis
			\| publisher = [[Academic Press]]
			\| year = 1979
			\| isbn = 0-12-471252-5
			}} Especially chapters 11 and 12.</ref>
			:<math>\mathbf{T} = \mathbf{W} + \mathbf{B},</math>
			where '''T''' is the total sum of squares and products (SSP) [[Matrix (mathematics)\|matrix]], '''W''' is the within-samples SSP matrix and '''B''' is the between-samples SSP matrix.
			Similar terminology may also be used in [[linear discriminant analysis]], where '''W''' and '''B''' are respectively referred to as the within-groups and between-groups SSP matrics.<ref name="MardiaK1979Multivariate"/>

			==See also==
			*[[Sum of squares (statistics)]]
			*[[Lack-of-fit sum of squares]]

			==References==
			{{Reflist}}

			[[Category:Regression analysis]]
			[[Category:Least squares]]

en>Andrewaskew: Fixed order of categorisation.

2012-07-03T01:52:36Z

Fixed order of categorisation.

New page

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