Multinomial mixture probabilities

This is equivalent to performing the initial "E" step in expectation maximisation (EM) for a multinomial mixture model.

multinomial_mix(target, profiles)

Arguments

target	A vector of citations to be compared
profiles	A matrix of community_profile()s

Value

A vector of log-probabilities that each community generated target's citation profile.

Details

Here we are effectively computing the nearest point in the convex hull of community profiles, implicitly using Kullback--Leibler divergence as the distance measure. Alternative distance measures may be used; see nearest_point() and others.

See also

nearest_point()

Examples

# To which cluster should 'Biometrika' belong?
distances <- as.dist(1 - cor(citations + t(citations)))
clusters <- cutree(hclust(distances), h = 0.8)
profiles <- community_profile(citations, clusters)
Biometrika <- citations[, 'Bka']
w <- multinomial_mix(Biometrika, profiles)
which.max(w) == clusters['Bka']
#>  Bka 
#> TRUE 
profiles %*% exp(w) # nearest point
#> 47 x 1 Matrix of class "dgeMatrix"
#>                [,1]
#> AmS    5.126183e-03
#> AISM   9.266562e-03
#> AoS    1.784306e-01
#> ANZS   3.746057e-03
#> Bern   2.267350e-02
#> BioJ   5.520505e-03
#> Bcs    4.554416e-02
#> Bka    8.339905e-02
#> Biost  1.360410e-02
#> CJS    1.518139e-02
#> CSSC   2.168770e-03
#> CSTM   4.140379e-03
#> CmpSt  4.929022e-03
#> CSDA   3.253155e-02
#> EES    2.957413e-03
#> Envr   8.083596e-03
#> ISR    2.563091e-03
#> JABES  2.760252e-03
#> JASA   1.575315e-01
#> JAS    1.380126e-03
#> JBS    1.971609e-04
#> JCGS   2.996845e-02
#> JMA    2.858833e-02
#> JNS    1.123817e-02
#> JRSS-A 4.140379e-03
#> JRSS-B 9.641167e-02
#> JRSS-C 7.294953e-03
#> JSCS   5.914826e-03
#> JSPI   3.391167e-02
#> JSS    4.534700e-03
#> JTSA   2.957413e-03
#> LDA    4.140379e-03
#> Mtka   3.154574e-03
#> SJS    2.227918e-02
#> StataJ 3.290657e-98
#> StCmp  1.537855e-02
#> Stats  3.548896e-03
#> StMed  2.168770e-02
#> SMMR   1.774448e-03
#> StMod  3.351735e-03
#> StNee  3.746057e-03
#> StPap  5.914826e-04
#> SPL    1.892744e-02
#> StSci  1.912461e-02
#> StSin  3.588328e-02
#> Tech   1.025237e-02
#> Test   9.463722e-03