Programmer Guide/Command Reference/EVAL/dist - Revision history

Christian at 18:23, 21 April 2011

2011-04-21T18:23:47Z

← Older revision		Revision as of 20:23, 21 April 2011
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	;Result 2: The matrix ''d'' with the euclidian distances of all elements or row vectors of ''x''. The result is a matrix with <code>nrow(''x'')</code> rows and columns.		;Result 2: The matrix ''d'' with the euclidian distances of all elements or row vectors of ''x''. The result is a matrix with <code>nrow(''x'')</code> rows and columns.
	:{\|class="keinrahmen"		:{\|class="keinrahmen"
	\|''x''<sub>vector</sub> \|\|-> ''d''[i,j] = dist(''x''[i], ''x''[j])		\|''x''<sub>vector</sub> \|\|→ ''d''[i,j] = dist(''x''[i], ''x''[j])
	\|-		\|-
	\|''x''<sub>matrix</sub> \|\|-> ''d''[i,j] = dist(''x''[i,], ''x''[j,])		\|''x''<sub>matrix</sub> \|\|→ ''d''[i,j] = dist(''x''[i,], ''x''[j,])
	\|-		\|-
	\| \|\| with: i,j = 0 .. <code>ncol(''x'')</code>		\| \|\| with: i,j = 0 .. <code>ncol(''x'')</code>
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	;Result 3: The vector ''d'' with the euclidian distances of all elements or row vectors of ''x'' to ''y''. The result is a vector with <code>nrow(''x'')</code> rows and columns.		;Result 3: The vector ''d'' with the euclidian distances of all elements or row vectors of ''x'' to ''y''. The result is a vector with <code>nrow(''x'')</code> rows and columns.
	:{\|class="keinrahmen"		:{\|class="keinrahmen"
	\|''x''<sub>vector</sub>,''y''<sub>scalar</sub> \|\|-> ''d''[i] = dist(''x''[i], ''y'')		\|''x''<sub>vector</sub>,''y''<sub>scalar</sub> \|\|→ ''d''[i] = dist(''x''[i], ''y'')
	\|-		\|-
	\|''x''<sub>matrix</sub>,''y''<sub>vector</sub> \|\|-> ''d''[i,j] = dist(''x''[i,*], ''y'') (<code>ncol(''x'')</code> must be equal to <code>nrow(''y'')</code>!)		\|''x''<sub>matrix</sub>,''y''<sub>vector</sub> \|\|→ ''d''[i,j] = dist(''x''[i,*], ''y'') (<code>ncol(''x'')</code> must be equal to <code>nrow(''y'')</code>!)
	\|-		\|-
	\| \|\| with: i = 0 .. <code>ncol(''x'')</code>		\| \|\| with: i = 0 .. <code>ncol(''x'')</code>
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	;Result 4: The matrix ''d'' with the euclidian distances of the row vectors (''flag''='''0''') or column vectors (''flag''='''1''') or ''x''.		;Result 4: The matrix ''d'' with the euclidian distances of the row vectors (''flag''='''0''') or column vectors (''flag''='''1''') or ''x''.
	:{\|class="keinrahmen"		:{\|class="keinrahmen"
	\|''flag''=0 \|\|-> ''d''[i,j] = dist(''x''[i,], ''x[j,]'') \|\|, with: i,j = 0 .. <code>nrow(''x'')</code>		\|''flag''=0 \|\|→ ''d''[i,j] = dist(''x''[i,], ''x[j,]'') \|\|, with: i,j = 0 .. <code>nrow(''x'')</code>
	\|-		\|-
	\|''flag''=1 \|\|-> ''d''[i,j] = dist(''x''[,i], ''x[,j]'') \|\|, with: i,j = 0 .. <code>ncol(''x'')</code>		\|''flag''=1 \|\|→ ''d''[i,j] = dist(''x''[,i], ''x[,j]'') \|\|, with: i,j = 0 .. <code>ncol(''x'')</code>
	\|}		\|}
	----		----

193.171.195.48 at 09:35, 21 April 2011

2011-04-21T09:35:20Z

← Older revision		Revision as of 11:35, 21 April 2011
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	----		----
	;Usage 1:		;Usage 1:
	:~~'''~~<code>dist(''x''<sub>scalar</sub>, ''y''<sub>scalar</sub>)</code>~~'''~~		:<code>dist(''x''<sub>scalar</sub>, ''y''<sub>scalar</sub>)</code>
	:~~'''~~<code>dist(''x''<sub>vector</sub>, ''y''<sub>vector</sub>)</code>~~'''~~		:<code>dist(''x''<sub>vector</sub>, ''y''<sub>vector</sub>)</code>
	;Result 1: The euclidan distance ''d''<sub>scalar</sub> of ''x'' and ''y''. The two arguments must be scalars or vectors with the same length.		;Result 1: The euclidan distance ''d''<sub>scalar</sub> of ''x'' and ''y''. The two arguments must be scalars or vectors with the same length.
	----		----
	;Usage 2:		;Usage 2:
	:~~'''~~<code>dist(''x''<sub>vector</sub>)</code>~~'''~~		:<code>dist(''x''<sub>vector</sub>)</code>
	:~~'''~~<code>dist(''x''<sub>matrix</sub>)</code>~~'''~~		:<code>dist(''x''<sub>matrix</sub>)</code>
	;Result 2: The matrix ''d'' with the euclidian distances of all elements or row vectors of ''x''. The result is a matrix with <code>nrow(''x'')</code> rows and columns.		;Result 2: The matrix ''d'' with the euclidian distances of all elements or row vectors of ''x''. The result is a matrix with <code>nrow(''x'')</code> rows and columns.
	:{\|class="keinrahmen"		:{\|class="keinrahmen"
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	----		----
	;Usage 3:		;Usage 3:
	:~~'''~~<code>dist(''x''<sub>vector</sub>, ''y''<sub>scalar</sub>)</code>~~'''~~		:<code>dist(''x''<sub>vector</sub>, ''y''<sub>scalar</sub>)</code>
	:~~'''~~<code>dist(''x''<sub>matrix</sub>, ''y''<sub>vector</sub>)</code>~~'''~~		:<code>dist(''x''<sub>matrix</sub>, ''y''<sub>vector</sub>)</code>
	;Result 3: The vector ''d'' with the euclidian distances of all elements or row vectors of ''x'' to ''y''. The result is a vector with <code>nrow(''x'')</code> rows and columns.		;Result 3: The vector ''d'' with the euclidian distances of all elements or row vectors of ''x'' to ''y''. The result is a vector with <code>nrow(''x'')</code> rows and columns.
	:{\|class="keinrahmen"		:{\|class="keinrahmen"
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	----		----
	;Usage 4:		;Usage 4:
	:~~'''~~<code>dist(''x''<sub>matrix</sub>, ''flag'')</code>~~'''~~		:<code>dist(''x''<sub>matrix</sub>, ''flag'')</code>
	;Result 4: The matrix ''d'' with the euclidian distances of the row vectors (''flag''='''0''') or column vectors (''flag''='''1''') or ''x''.		;Result 4: The matrix ''d'' with the euclidian distances of the row vectors (''flag''='''0''') or column vectors (''flag''='''1''') or ''x''.
	:{\|class="keinrahmen"		:{\|class="keinrahmen"
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	\|}		\|}
	----		----
	;See also: [[~~Programmer_Guide/Command_Reference/EVAL~~/var\|var]], [[~~Programmer_Guide/Command_Reference/EVAL~~/corr\|corr]]		;See also: [[../var\|var]], [[../corr\|corr]], [[../haclust\|haclust]]

	[[~~Programmer_Guide~~/~~Command_Reference/EVAL~~#Functions\|<function list>]]		[[../#Functions\|<function list>]]

Toni at 09:58, 20 April 2011

2011-04-20T09:58:40Z

← Older revision		Revision as of 11:58, 20 April 2011
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	{{DISPLAYTITLE:{{SUBPAGENAME}}}}		{{DISPLAYTITLE:{{SUBPAGENAME}}}}
	Compute the ~~variance, covariance~~ or ~~covariance~~-matrix.		Compute the distance or distance-matrix.
	----		----
	;Usage 1:		;Usage 1:

Toni at 09:58, 20 April 2011

2011-04-20T09:58:03Z

← Older revision		Revision as of 11:58, 20 April 2011
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	\|''flag''=1 \|\|-> ''d''[i,j] = dist(''x''[,i], ''x[,j]'') \|\|, with: i,j = 0 .. <code>ncol(''x'')</code>		\|''flag''=1 \|\|-> ''d''[i,j] = dist(''x''[,i], ''x[,j]'') \|\|, with: i,j = 0 .. <code>ncol(''x'')</code>
	\|}		\|}
			----

	;See also: [[Programmer_Guide/Command_Reference/EVAL/var\|var]], [[Programmer_Guide/Command_Reference/EVAL/corr\|corr]]		;See also: [[Programmer_Guide/Command_Reference/EVAL/var\|var]], [[Programmer_Guide/Command_Reference/EVAL/corr\|corr]]

	[[Programmer_Guide/Command_Reference/EVAL#Functions\|<function list>]]		[[Programmer_Guide/Command_Reference/EVAL#Functions\|<function list>]]

Toni at 08:47, 11 April 2011

2011-04-11T08:47:08Z

← Older revision		Revision as of 10:47, 11 April 2011
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	\|''x''<sub>vector</sub>,''y''<sub>scalar</sub> \|\|-> ''d''[i] = dist(''x''[i], ''y'')		\|''x''<sub>vector</sub>,''y''<sub>scalar</sub> \|\|-> ''d''[i] = dist(''x''[i], ''y'')
	\|-		\|-
	\|''x''<sub>matrix</sub>,''y''<sub>vector</sub> \|\|-> ''d''[i,j] = dist(''x''[i,*], ''y'') (<code>ncol(''x'')</code> must be equal to <code>nrow(''y'')</code>		\|''x''<sub>matrix</sub>,''y''<sub>vector</sub> \|\|-> ''d''[i,j] = dist(''x''[i,*], ''y'') (<code>ncol(''x'')</code> must be equal to <code>nrow(''y'')</code>!)
	\|-		\|-
	\| \|\| with: i = 0 .. <code>ncol(''x'')</code>		\| \|\| with: i = 0 .. <code>ncol(''x'')</code>

Toni at 08:46, 11 April 2011

2011-04-11T08:46:50Z

← Older revision		Revision as of 10:46, 11 April 2011
Line 26:		Line 26:
	\|''x''<sub>vector</sub>,''y''<sub>scalar</sub> \|\|-> ''d''[i] = dist(''x''[i], ''y'')		\|''x''<sub>vector</sub>,''y''<sub>scalar</sub> \|\|-> ''d''[i] = dist(''x''[i], ''y'')
	\|-		\|-
	\|''x''<sub>matrix</sub>,''y''<sub>vector</sub> \|\|-> ''d''[i,j] = dist(''x''[i,*], ''y'') (<code>ncol(''x'') = nrow(''y'')</code>		\|''x''<sub>matrix</sub>,''y''<sub>vector</sub> \|\|-> ''d''[i,j] = dist(''x''[i,*], ''y'') (<code>ncol(''x'')</code> must be equal to <code>nrow(''y'')</code>
	\|-		\|-
	\| \|\| with: i = 0 .. <code>ncol(''x'')</code>		\| \|\| with: i = 0 .. <code>ncol(''x'')</code>
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	;Usage 4:		;Usage 4:
	:'''<code>dist(''x''<sub>matrix</sub>, ''flag'')</code>'''		:'''<code>dist(''x''<sub>matrix</sub>, ''flag'')</code>'''
	;Result 3: The matrix ''d'' with the euclidian distances of the row vectors (''flag''='''0''') or column vectors (''flag''='''1''') or ''x''.		;Result 4: The matrix ''d'' with the euclidian distances of the row vectors (''flag''='''0''') or column vectors (''flag''='''1''') or ''x''.
	:{\|class="keinrahmen"		:{\|class="keinrahmen"
	\|''flag''=0 \|\|-> ''d''[i,j] = dist(''x''[i,], ''x[j,]'') \|\|, with: i,j = 0 .. <code>nrow(''x'')</code>		\|''flag''=0 \|\|-> ''d''[i,j] = dist(''x''[i,], ''x[j,]'') \|\|, with: i,j = 0 .. <code>nrow(''x'')</code>

Toni at 08:45, 11 April 2011

2011-04-11T08:45:16Z

@@ Line 10: / Line 10: @@
 :'''<code>dist(''x''<sub>vector</sub>)</code>'''
 :'''<code>dist(''x''<sub>matrix</sub>)</code>'''
-;Result 2: The distance matrix ''d'' with the euclidian distances of all elements or row vectors of ''x''. The result is a matrix with <code>nrow(''x'')</code> rows and columns.
+;Result 2: The matrix ''d'' with the euclidian distances of all elements or row vectors of ''x''. The result is a matrix with <code>nrow(''x'')</code> rows and columns.
 :{|class="keinrahmen"
 |''x''<sub>vector</sub> ||-> ''d''[i,j] = dist(''x''[i], ''x''[j])
 |-
-|''x''<sub>matrix</sub> ||-> ''d''<sub>i,j</sub> = dist(''x''[i,*], ''x''[j,*])
+|''x''<sub>matrix</sub> ||-> ''d''[i,j] = dist(''x''[i,*], ''x''[j,*])
 |}
 ----
-;Usage 2: '''<code>dist(''x'')</code>'''
+;Usage 3:
-;Result 2:
+:'''<code>dist(''x''<sub>vector</sub>, ''y''<sub>scalar</sub>)</code>'''
-The covariance ''v'' of the vectors ''x'' and ''y''.
+:'''<code>dist(''x''<sub>matrix</sub>, ''y''<sub>vector</sub>)</code>'''
-:<code>''v'' = sum( (''x''-avr(''x'') ?* (''y''-avr(''y'')) ) / (nrow(''x'')-1)</code>
+;Result 3: The vector ''d'' with the euclidian distances of all elements or row vectors of ''x'' to ''y''. The result is a vector with <code>nrow(''x'')</code> rows and columns.
-:<code>''v'' = ((''x''-avr(''x'') * (''y''-avr(''y''))) / (nrow(''x'')-1)</code>
+:{|class="keinrahmen"
-----
+|''x''<sub>vector</sub>,''y''<sub>scalar</sub> ||-> ''d''[i] = dist(''x''[i], ''y'')
 |-
-|''y''<sub>scalar</sub> || a[i] = ''y''
+|''x''<sub>matrix</sub>,''y''<sub>vector</sub> ||-> ''d''[i,j] = dist(''x''[i,*], ''y'')  (<code>ncol(''x'') = nrow(''y'')</code>
 |-
-|''y''<sub>vector</sub> || a[i] = ''y''[i]
+| || with: i = 0 .. <code>ncol(''x'')</code>
 |-
 |}
-;See also: [[Programmer_Guide/Command_Reference/EVAL/avr|avr]], [[Programmer_Guide/Command_Reference/EVAL/dev|dev]], [[Programmer_Guide/Command_Reference/EVAL/corr|corr]], [[Programmer_Guide/Command_Reference/EVAL/dist|dist]]
 [[Programmer_Guide/Command_Reference/EVAL#Functions|<function list>]]

Toni at 08:34, 11 April 2011

2011-04-11T08:34:53Z

← Older revision		Revision as of 10:34, 11 April 2011
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	;Result 2: The distance matrix ''d'' with the euclidian distances of all elements or row vectors of ''x''. The result is a matrix with <code>nrow(''x'')</code> rows and columns.		;Result 2: The distance matrix ''d'' with the euclidian distances of all elements or row vectors of ''x''. The result is a matrix with <code>nrow(''x'')</code> rows and columns.
	:{\|class="keinrahmen"		:{\|class="keinrahmen"
	\| ''x''<sub>vector</sub> \|-> ''d''[i,j] = dist(''x''[i], ''x''[j])		\|''x''<sub>vector</sub> \|\|-> ''d''[i,j] = dist(''x''[i], ''x''[j])
	\|-		\|-
	\| ''x''<sub>matrix</sub> \|-> ''d''<sub>i,j</sub> = dist(''x''[i,], ''x''[j,])		\|''x''<sub>matrix</sub> \|\|-> ''d''<sub>i,j</sub> = dist(''x''[i,], ''x''[j,])
	\|}		\|}
	----		----

Toni at 08:33, 11 April 2011

2011-04-11T08:33:59Z

← Older revision		Revision as of 10:33, 11 April 2011
Line 1:		Line 1:
			{{DISPLAYTITLE:{{SUBPAGENAME}}}}
			Compute the variance, covariance or covariance-matrix.
			----
			;Usage 1:
			:'''<code>dist(''x''<sub>scalar</sub>, ''y''<sub>scalar</sub>)</code>'''
			:'''<code>dist(''x''<sub>vector</sub>, ''y''<sub>vector</sub>)</code>'''
			;Result 1: The euclidan distance ''d''<sub>scalar</sub> of ''x'' and ''y''. The two arguments must be scalars or vectors with the same length.
			----
			;Usage 2:
			:'''<code>dist(''x''<sub>vector</sub>)</code>'''
			:'''<code>dist(''x''<sub>matrix</sub>)</code>'''
			;Result 2: The distance matrix ''d'' with the euclidian distances of all elements or row vectors of ''x''. The result is a matrix with <code>nrow(''x'')</code> rows and columns.
			:{\|class="keinrahmen"
			\| ''x''<sub>vector</sub> \|-> ''d''[i,j] = dist(''x''[i], ''x''[j])
			\|-
			\| ''x''<sub>matrix</sub> \|-> ''d''<sub>i,j</sub> = dist(''x''[i,], ''x''[j,])
			\|}
			----
			;Usage 2: '''<code>dist(''x'')</code>'''
			;Result 2:
			The covariance ''v'' of the vectors ''x'' and ''y''.
			:<code>''v'' = sum( (''x''-avr(''x'') ?* (''y''-avr(''y'')) ) / (nrow(''x'')-1)</code>
			:<code>''v'' = ((''x''-avr(''x'') * (''y''-avr(''y''))) / (nrow(''x'')-1)</code>
			----
			;Usage 3: '''<code>var(''x''<sub>matrix</sub>)</code>'''
			:'''<code>var(''x''<sub>matrix</sub>, ''y''<sub>scalar</sub>)</code>'''
			:'''<code>var(''x''<sub>matrix</sub>, ''y''<sub>vector</sub>)</code>'''
			;Result 3: The covariance matrix ''v'' of the column vectors of ''x''.
			:<code>''v''[i,j] = sum( (''x''[,i]-a[i]) ? (''x''[*,j]-a[j]) ) / (nrow(''x'')-1) , with: i,j = 0..ncol(''x'')-1</code>
			:The column averages a[i] are computed as follows:
			::{\|class="einrahmen"
			\|''y'' not supplied \|\| a[i] = avr(''x''[*,i])
			\|-
			\|''y''<sub>scalar</sub> \|\| a[i] = ''y''
			\|-
			\|''y''<sub>vector</sub> \|\| a[i] = ''y''[i]
			\|-
			\|}

			;See also: [[Programmer_Guide/Command_Reference/EVAL/avr\|avr]], [[Programmer_Guide/Command_Reference/EVAL/dev\|dev]], [[Programmer_Guide/Command_Reference/EVAL/corr\|corr]], [[Programmer_Guide/Command_Reference/EVAL/dist\|dist]]

			[[Programmer_Guide/Command_Reference/EVAL#Functions\|<function list>]]



	{{DISPLAYTITLE:{{SUBPAGENAME}}}}		{{DISPLAYTITLE:{{SUBPAGENAME}}}}
	=====dist=====		=====dist=====

Admin: 1 revision: Initial import

2010-11-18T16:31:40Z

1 revision: Initial import

← Older revision	Revision as of 18:31, 18 November 2010
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