ABOUT: "math.statistics"
-{ var full-var sample-var } related-words
-{ std full-std sample-std } related-words
-{ ste full-ste sample-ste } related-words
-{ corr full-corr sample-corr } related-words
+{ var population-var sample-var } related-words
+{ std population-std sample-std } related-words
+{ ste population-ste sample-ste } related-words
+{ corr population-corr sample-corr } related-words
[ 1 ] [ { 1 2 3 } var ] unit-test
[ 16 ] [ { 4 6 8 10 10 12 14 16 } var ] unit-test
-{ 16 } [ { 4 6 8 10 12 14 16 } full-var ] unit-test
+{ 16 } [ { 4 6 8 10 12 14 16 } population-var ] unit-test
{ 1.0 } [ { 7 8 9 } std ] unit-test
{ 2/3 } [ { 7 8 9 } 0 var-ddof ] unit-test
-{ 2/3 } [ { 7 8 9 } full-var ] unit-test
+{ 2/3 } [ { 7 8 9 } population-var ] unit-test
{ 1 } [ { 7 8 9 } 1 var-ddof ] unit-test
{ 1 } [ { 7 8 9 } var ] unit-test
{ 1 } [ { 7 8 9 } sample-var ] unit-test
{ 0 } [ { 7 8 9 } 3 var-ddof ] unit-test
{ t } [ { 7 8 9 } 0 std-ddof 0.816496580927726 .0001 ~ ] unit-test
-{ t } [ { 7 8 9 } full-std 0.816496580927726 .0001 ~ ] unit-test
+{ t } [ { 7 8 9 } population-std 0.816496580927726 .0001 ~ ] unit-test
{ 1.0 } [ { 7 8 9 } 1 std-ddof ] unit-test
{ 1.0 } [ { 7 8 9 } std ] unit-test
{ 1.0 } [ { 7 8 9 } sample-std ] unit-test
[ [ sum-of-squared-errors ] [ length ] bi ] dip - /
] if ; inline
-: full-var ( seq -- x ) 0 var-ddof ; inline
-
+: population-var ( seq -- x ) 0 var-ddof ; inline
+
: sample-var ( seq -- x ) 1 var-ddof ; inline
ALIAS: var sample-var
: std-ddof ( seq n -- x )
var-ddof sqrt ; inline
-: full-std ( seq -- x ) 0 std-ddof ; inline
+: population-std ( seq -- x ) 0 std-ddof ; inline
: sample-std ( seq -- x ) 1 std-ddof ; inline
: ste-ddof ( seq n -- x ) '[ _ std-ddof ] [ length ] bi sqrt / ;
-: full-ste ( seq -- x ) 0 ste-ddof ;
+: population-ste ( seq -- x ) 0 ste-ddof ;
: sample-ste ( seq -- x ) 1 ste-ddof ;
[ [ cov ] ] dip
'[ [ _ var-ddof ] bi@ * sqrt ] 2bi / ;
-: full-corr ( {x} {y} -- corr ) 0 corr-ddof ; inline
+: population-corr ( {x} {y} -- corr ) 0 corr-ddof ; inline
: sample-corr ( {x} {y} -- corr ) 1 corr-ddof ; inline
v- norm 1 + recip ;
: pearson-similarity ( a b -- n )
- over length 3 < [ 2drop 1.0 ] [ full-corr 0.5 * 0.5 + ] if ;
+ over length 3 < [ 2drop 1.0 ] [ population-corr 0.5 * 0.5 + ] if ;
: cosine-similarity ( a b -- n )
[ v* sum ] [ [ norm ] bi@ * ] 2bi / 0.5 * 0.5 + ;