Motifs
Functions for calculating subgraphs in multimodal networks. These functions have an additional dimension than node_ and network_ measures and marks that capture the different motifs surveyed.
Marking nodes based on their properties
node_is_random(.data, size = 1) +node_is_mentor(.data, elites = 0.1) + node_is_max(node_measure, ranks = 1) node_is_min(node_measure, ranks = 1) @@ -103,6 +105,21 @@Arguments
The number of nodes to select (as TRUE).
The proportion of nodes to be selected as mentors. +By default this is set at 0.1. +This means that the top 10% of nodes in terms of degree, +or those equal to the highest rank degree in the network, +whichever is the higher, will be used to select the mentors.
+Note that if nodes are equidistant from two mentors, +they will choose one at random. +If a node is without a path to a mentor, +for example because they are an isolate, +a tie to themselves (a loop) will be created instead. +Note that this is a different default behaviour than that +described in Valente and Davis (1999).
An object created by a node_ measure.
Functions
of the core of the network.node_is_random(): Returns a logical vector
indicating a random selection of nodes as TRUE.
node_is_mentor(): Returns a logical vector
+indicating mentor (high indegree) nodes as TRUE.
node_is_max(): Returns logical of which nodes
hold the maximum of some measure
node_is_min(): Returns logical of which nodes
hold the minimum of some measure
+
References
+Valente, Thomas, and Rebecca Davis. 1999. +"Accelerating the Diffusion of Innovations Using Opinion Leaders", +Annals of the American Academy of Political and Social Science 566: 56-67.
+See also
Other marks: @@ -152,7 +177,7 @@
Examples
#> 1 FALSE FALSE TRUE TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE node_is_random(ison_brandes, 2) #> V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 -#> 1 FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE +#> 1 FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE FALSE node_is_max(node_degree(ison_brandes)) #> V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 #> 1 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE diff --git a/reference/mark_ties.html b/reference/mark_ties.html index 0b2197ec..e2a56c16 100644 --- a/reference/mark_ties.html +++ b/reference/mark_ties.html @@ -20,7 +20,7 @@Examples
task_eg <- manynet::to_named(manynet::to_uniplex(manynet::ison_algebra, "task_tie"))
(tie_cen <- node_tie_census(task_eg))
#> # A tibble: 16 × 33
-#> names fromSydney fromMonique fromJoan fromTucker fromAnnie fromTammie
-#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
-#> 1 Sydney 0 1 0 0 1 1
-#> 2 Monique 0 0 1 0 0 0
-#> 3 Joan 0 1 0 0 1 1
-#> 4 Tucker 0 0 0 0 0 0
-#> 5 Annie 1 0 1 0 0 1
-#> 6 Tammie 0 0 1 0 1 0
-#> 7 Marco 0 1 1 0 0 1
-#> 8 Eileen 1 1 1 0 1 1
-#> 9 Lester 1 0 0 0 0 0
-#> 10 Claude 1 0 1 1 1 1
-#> 11 Isabel 1 0 1 0 1 1
-#> 12 Christopher 1 1 0 0 0 1
-#> 13 Alexander 1 1 0 0 1 0
-#> 14 Karl 0 1 1 0 0 1
-#> 15 Maximus 1 1 1 0 1 0
-#> 16 Chelsey 1 1 1 1 1 1
-#> # ℹ 26 more variables: fromMarco <dbl>, fromEileen <dbl>, fromLester <dbl>,
-#> # fromClaude <dbl>, fromIsabel <dbl>, fromChristopher <dbl>,
-#> # fromAlexander <dbl>, fromKarl <dbl>, fromMaximus <dbl>, fromChelsey <dbl>,
-#> # toSydney <dbl>, toMonique <dbl>, toJoan <dbl>, toTucker <dbl>,
-#> # toAnnie <dbl>, toTammie <dbl>, toMarco <dbl>, toEileen <dbl>,
-#> # toLester <dbl>, toClaude <dbl>, toIsabel <dbl>, toChristopher <dbl>,
-#> # toAlexander <dbl>, toKarl <dbl>, toMaximus <dbl>, toChelsey <dbl>
+#> names fromJose fromGeraldine fromMarissa fromColton fromHeidi fromChristopher
+#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1 Jose 0 1 0 0 1 1
+#> 2 Gera… 0 0 1 0 0 0
+#> 3 Mari… 0 1 0 0 1 1
+#> 4 Colt… 0 0 0 0 0 0
+#> 5 Heidi 1 0 1 0 0 1
+#> 6 Chri… 0 0 1 0 1 0
+#> 7 Flos… 0 1 1 0 0 1
+#> 8 Rosa 1 1 1 0 1 1
+#> 9 Etta 1 0 0 0 0 0
+#> 10 Mere… 1 0 1 1 1 1
+#> 11 Darl… 1 0 1 0 1 1
+#> 12 Cole 1 1 0 0 0 1
+#> 13 Alexa 1 1 0 0 1 0
+#> 14 Micah 0 1 1 0 0 1
+#> 15 Xand… 1 1 1 0 1 0
+#> 16 Alice 1 1 1 1 1 1
+#> # ℹ 26 more variables: fromFlossie <dbl>, fromRosa <dbl>, fromEtta <dbl>,
+#> # fromMeredith <dbl>, fromDarlene <dbl>, fromCole <dbl>, fromAlexa <dbl>,
+#> # fromMicah <dbl>, fromXander <dbl>, fromAlice <dbl>, toJose <dbl>,
+#> # toGeraldine <dbl>, toMarissa <dbl>, toColton <dbl>, toHeidi <dbl>,
+#> # toChristopher <dbl>, toFlossie <dbl>, toRosa <dbl>, toEtta <dbl>,
+#> # toMeredith <dbl>, toDarlene <dbl>, toCole <dbl>, toAlexa <dbl>,
+#> # toMicah <dbl>, toXander <dbl>, toAlice <dbl>
(triad_cen <- node_triad_census(task_eg))
#> # A tibble: 16 × 17
#> names X003 X012 X102 X021D X021U X021C X111D X111U X030T X030C X201 X120D
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
-#> 1 Sydn… 6 12 32 0 1 0 7 3 0 0 8 1
-#> 2 Moni… 15 12 42 0 0 0 0 5 0 0 4 1
-#> 3 Joan 20 5 37 0 0 0 3 3 0 0 12 0
-#> 4 Tuck… 102 0 3 0 0 0 0 0 0 0 0 0
-#> 5 Annie 15 5 41 0 0 0 2 1 0 0 13 0
-#> 6 Tamm… 20 5 41 0 0 0 3 2 0 0 11 0
-#> 7 Marco 28 0 51 0 0 0 0 2 0 0 6 0
-#> 8 Eile… 18 0 42 0 0 0 2 1 0 0 18 0
-#> 9 Lest… 86 2 17 0 0 0 0 0 0 0 0 0
-#> 10 Clau… 25 6 35 0 0 0 3 3 0 0 15 0
-#> 11 Isab… 65 4 36 0 0 0 0 0 0 0 0 0
-#> 12 Chri… 72 3 30 0 0 0 0 0 0 0 0 0
-#> 13 Alex… 76 3 26 0 0 0 0 0 0 0 0 0
-#> 14 Karl 56 2 47 0 0 0 0 0 0 0 0 0
-#> 15 Maxi… 58 5 42 0 0 0 0 0 0 0 0 0
-#> 16 Chel… 0 0 0 0 0 0 0 0 0 0 44 0
+#> 1 Jose 6 12 32 0 1 0 7 3 0 0 8 1
+#> 2 Gera… 15 12 42 0 0 0 0 5 0 0 4 1
+#> 3 Mari… 20 5 37 0 0 0 3 3 0 0 12 0
+#> 4 Colt… 102 0 3 0 0 0 0 0 0 0 0 0
+#> 5 Heidi 15 5 41 0 0 0 2 1 0 0 13 0
+#> 6 Chri… 20 5 41 0 0 0 3 2 0 0 11 0
+#> 7 Flos… 28 0 51 0 0 0 0 2 0 0 6 0
+#> 8 Rosa 18 0 42 0 0 0 2 1 0 0 18 0
+#> 9 Etta 86 2 17 0 0 0 0 0 0 0 0 0
+#> 10 Mere… 25 6 35 0 0 0 3 3 0 0 15 0
+#> 11 Darl… 65 4 36 0 0 0 0 0 0 0 0 0
+#> 12 Cole 72 3 30 0 0 0 0 0 0 0 0 0
+#> 13 Alexa 76 3 26 0 0 0 0 0 0 0 0 0
+#> 14 Micah 56 2 47 0 0 0 0 0 0 0 0 0
+#> 15 Xand… 58 5 42 0 0 0 0 0 0 0 0 0
+#> 16 Alice 0 0 0 0 0 0 0 0 0 0 44 0
#> # ℹ 4 more variables: X120U <dbl>, X120C <dbl>, X210 <dbl>, X300 <dbl>
node_quad_census(manynet::ison_southern_women)
#> # A tibble: 32 × 13
diff --git a/reference/over.html b/reference/over.html
index aa7758be..346eda3f 100644
--- a/reference/over.html
+++ b/reference/over.html
@@ -17,7 +17,7 @@
Functions to play games on networks
attribute, heterophily = 0, who_moves = c("ordered", "random", "most_dissatisfied"), - choice_function = c("satisficing", "optimising"), + choice_function = c("satisficing", "optimising", "minimising"), steps ) @@ -127,7 +127,7 @@Arguments
A proportion indicating the transmission rate, +
The transmission rate probability, \(\beta\). By default 1, which means any node for which the threshold is met or exceeded will become infected. @@ -136,17 +136,17 @@
Arguments
A proportion indicating the rate at which those exposed -become infectious (infected), \(\sigma\). +
The inverse probability those who have been exposed +become infectious (infected), \(\sigma\) or \(\kappa\). For example, if exposed individuals take, on average, -four days to become infectious, then \(\sigma = 0.25\). +four days to become infectious, then \(\sigma = 0.75\) (1/1-0.75 = 1/0.25 = 4). By default 0, which means those exposed become immediately infectious (i.e. an SI model). Anything higher results in e.g. a SEI model.
A proportion indicating the rate of recovery, -\(\gamma\). +
The probability those who are infected +recover, \(\gamma\). For example, if infected individuals take, on average, four days to recover, then \(\gamma = 0.25\). By default 0, which means there is no recovery (i.e. an SI model). @@ -154,8 +154,8 @@
Arguments
A proportion indicating the rate at which those who are -recovered become susceptible again, \(\xi\). +
The probability those who are recovered +become susceptible again, \(\xi\). For example, if recovered individuals take, on average, four days to lose their immunity, then \(\xi = 0.25\). By default 0, which means any recovered individuals retain lifelong immunity (i.e. an SIR model). @@ -241,7 +241,8 @@
Arguments
One of the following options: "satisficing" (the default) will move the node to any coordinates that satisfy their heterophily threshold, -whereas "optimising" will move the node to coordinates that are most homophilous.
@@ -267,43 +268,42 @@ 
plot(play_diffusions(smeg, times = 20))
-#> Warning: Removed 24 rows containing missing values (`geom_smooth()`).
-#> Warning: Removed 51 rows containing missing values (`geom_smooth()`).
play_learning(ison_networkers,
rbinom(manynet::network_nodes(ison_networkers),1,prob = 0.25))
-#> # A tibble: 7 × 32
-#> `LIN FREEMAN` `DOUG WHITE` `EV ROGERS` `RICHARD ALBA` `PHIPPS ARABIE`
+#> # A tibble: 8 × 32
+#> `Lin Freeman` `Doug White` `Ev Rogers` `Richard Alba` `Phipps Arabie`
#> <dbl> <dbl> <dbl> <dbl> <dbl>
-#> 1 0 0 1 0 0
-#> 2 0.177 0.236 0 0.0755 0.181
-#> 3 0.157 0.150 0.178 0.164 0.154
-#> 4 0.150 0.155 0.150 0.150 0.150
-#> 5 0.153 0.151 0.151 0.152 0.152
-#> 6 0.151 0.152 0.152 0.152 0.151
-#> 7 0.152 0.151 0.151 0.152 0.152
-#> # ℹ 27 more variables: `CAROL BARNER-BARRY` <dbl>, `GARY COOMBS` <dbl>,
-#> # `RUSS BERNARD` <dbl>, `JOHN BOYD` <dbl>, `RON BURT` <dbl>,
-#> # `PAT DOREIAN` <dbl>, `CLAUDE FISCHER` <dbl>, `BRIAN FOSTER` <dbl>,
-#> # `MARK GRANOVETTER` <dbl>, `MAUREEN HALLINAN` <dbl>, `PAUL HOLLAND` <dbl>,
-#> # `JACK HUNTER` <dbl>, `DAVOR JEDLICKA` <dbl>, `CHARLES KADUSHIN` <dbl>,
-#> # `ED LAUMANN` <dbl>, `SAM LEINHARDT` <dbl>, `JOEL LEVINE` <dbl>,
-#> # `NAN LIN` <dbl>, `NICK MULLINS` <dbl>, `DON PLOCH` <dbl>, …
+#> 1 0 0 1 0 0
+#> 2 0.198 0.181 0 0.263 0.258
+#> 3 0.165 0.179 0.186 0.165 0.156
+#> 4 0.182 0.177 0.167 0.183 0.184
+#> 5 0.176 0.179 0.181 0.178 0.176
+#> 6 0.178 0.178 0.177 0.178 0.179
+#> 7 0.178 0.178 0.178 0.178 0.178
+#> 8 0.178 0.178 0.178 0.178 0.178
+#> # ℹ 27 more variables: `Carol Barner-Barry` <dbl>, `Gary Coombs` <dbl>,
+#> # `Russ Bernard` <dbl>, `John Boyd` <dbl>, `Ron Burt` <dbl>,
+#> # `Pat Doreian` <dbl>, `Claude Fischer` <dbl>, `Brian Foster` <dbl>,
+#> # `Mark Granovetter` <dbl>, `Maureen Hallinan` <dbl>, `Paul Holland` <dbl>,
+#> # `Jack Hunter` <dbl>, `Davor Jedlicka` <dbl>, `Charles Kadushin` <dbl>,
+#> # `Ed Laumann` <dbl>, `Sam Leinhardt` <dbl>, `Joel Levine` <dbl>,
+#> # `Nan Lin` <dbl>, `Nick Mullins` <dbl>, `Don Ploch` <dbl>, …
startValues <- rbinom(100,1,prob = 0.5)
startValues[sample(seq_len(100), round(100*0.2))] <- NA
latticeEg <- manynet::create_lattice(100)
latticeEg <- manynet::add_node_attribute(latticeEg, "startValues", startValues)
latticeEg
-#> # A undirected tbl_graph with 100 nodes and 342 ties
+#> # A undirected network with 100 nodes and 342 ties
#> # A tibble: 100 × 1
#> startValues
#> <int>
-#> 1 0
+#> 1 NA
#> 2 NA
-#> 3 NA
+#> 3 0
#> 4 0
#> 5 1
-#> 6 0
+#> 6 NA
#> # ℹ 94 more rows
#> # A tibble: 342 × 2
#> from to
@@ -316,26 +316,21 @@
diff --git a/reference/reexports.html b/reference/reexports.html
index 9097a255..d50f2a66 100644
--- a/reference/reexports.html
+++ b/reference/reexports.html
@@ -44,7 +44,7 @@
diff --git a/reference/regression-1.png b/reference/regression-1.png
index 26cdb393..815160ee 100644
Binary files a/reference/regression-1.png and b/reference/regression-1.png differ
diff --git a/reference/regression.html b/reference/regression.html
index 50aa1035..43402b93 100644
--- a/reference/regression.html
+++ b/reference/regression.html
@@ -39,7 +39,7 @@
@@ -209,8 +209,8 @@ Examples
plot(play_diffusion(smeg, recovery = 0.4))
plot(play_diffusions(smeg, times = 20))
-#> Warning: Removed 24 rows containing missing values (`geom_smooth()`).
-#> Warning: Removed 51 rows containing missing values (`geom_smooth()`).
play_learning(ison_networkers,
rbinom(manynet::network_nodes(ison_networkers),1,prob = 0.25))
-#> # A tibble: 7 × 32
-#> `LIN FREEMAN` `DOUG WHITE` `EV ROGERS` `RICHARD ALBA` `PHIPPS ARABIE`
+#> # A tibble: 8 × 32
+#> `Lin Freeman` `Doug White` `Ev Rogers` `Richard Alba` `Phipps Arabie`
#> <dbl> <dbl> <dbl> <dbl> <dbl>
-#> 1 0 0 1 0 0
-#> 2 0.177 0.236 0 0.0755 0.181
-#> 3 0.157 0.150 0.178 0.164 0.154
-#> 4 0.150 0.155 0.150 0.150 0.150
-#> 5 0.153 0.151 0.151 0.152 0.152
-#> 6 0.151 0.152 0.152 0.152 0.151
-#> 7 0.152 0.151 0.151 0.152 0.152
-#> # ℹ 27 more variables: `CAROL BARNER-BARRY` <dbl>, `GARY COOMBS` <dbl>,
-#> # `RUSS BERNARD` <dbl>, `JOHN BOYD` <dbl>, `RON BURT` <dbl>,
-#> # `PAT DOREIAN` <dbl>, `CLAUDE FISCHER` <dbl>, `BRIAN FOSTER` <dbl>,
-#> # `MARK GRANOVETTER` <dbl>, `MAUREEN HALLINAN` <dbl>, `PAUL HOLLAND` <dbl>,
-#> # `JACK HUNTER` <dbl>, `DAVOR JEDLICKA` <dbl>, `CHARLES KADUSHIN` <dbl>,
-#> # `ED LAUMANN` <dbl>, `SAM LEINHARDT` <dbl>, `JOEL LEVINE` <dbl>,
-#> # `NAN LIN` <dbl>, `NICK MULLINS` <dbl>, `DON PLOCH` <dbl>, …
+#> 1 0 0 1 0 0
+#> 2 0.198 0.181 0 0.263 0.258
+#> 3 0.165 0.179 0.186 0.165 0.156
+#> 4 0.182 0.177 0.167 0.183 0.184
+#> 5 0.176 0.179 0.181 0.178 0.176
+#> 6 0.178 0.178 0.177 0.178 0.179
+#> 7 0.178 0.178 0.178 0.178 0.178
+#> 8 0.178 0.178 0.178 0.178 0.178
+#> # ℹ 27 more variables: `Carol Barner-Barry` <dbl>, `Gary Coombs` <dbl>,
+#> # `Russ Bernard` <dbl>, `John Boyd` <dbl>, `Ron Burt` <dbl>,
+#> # `Pat Doreian` <dbl>, `Claude Fischer` <dbl>, `Brian Foster` <dbl>,
+#> # `Mark Granovetter` <dbl>, `Maureen Hallinan` <dbl>, `Paul Holland` <dbl>,
+#> # `Jack Hunter` <dbl>, `Davor Jedlicka` <dbl>, `Charles Kadushin` <dbl>,
+#> # `Ed Laumann` <dbl>, `Sam Leinhardt` <dbl>, `Joel Levine` <dbl>,
+#> # `Nan Lin` <dbl>, `Nick Mullins` <dbl>, `Don Ploch` <dbl>, …
startValues <- rbinom(100,1,prob = 0.5)
startValues[sample(seq_len(100), round(100*0.2))] <- NA
latticeEg <- manynet::create_lattice(100)
latticeEg <- manynet::add_node_attribute(latticeEg, "startValues", startValues)
latticeEg
-#> # A undirected tbl_graph with 100 nodes and 342 ties
+#> # A undirected network with 100 nodes and 342 ties
#> # A tibble: 100 × 1
#> startValues
#> <int>
-#> 1 0
+#> 1 NA
#> 2 NA
-#> 3 NA
+#> 3 0
#> 4 0
#> 5 1
-#> 6 0
+#> 6 NA
#> # ℹ 94 more rows
#> # A tibble: 342 × 2
#> from to
@@ -316,26 +316,21 @@ Examples
#> 6 2 12 #> # ℹ 336 more rows play_segregation(latticeEg, "startValues", 0.5) -#> [1] "Moving node 5 to node 2" -#> [1] "Moving node 8 to node 3" -#> [1] "Moving node 46 to node 5" -#> [1] "Moving node 35 to node 8" -#> [1] "Moving node 54 to node 11" -#> [1] "Moving node 53 to node 20" -#> [1] "Moving node 70 to node 39" -#> [1] "Moving node 72 to node 50" -#> [1] "Moving node 40 to node 35" -#> [1] "Moving node 86 to node 37" -#> # A undirected tbl_graph with 100 nodes and 342 ties +#> [1] "Moving node 20 to node 57" +#> [1] "Moving node 23 to node 98" +#> [1] "Moving node 74 to node 48" +#> [1] "Moving node 81 to node 64" +#> [1] "Moving node 96 to node 41" +#> # A undirected network with 100 nodes and 342 ties #> # A tibble: 100 × 1 #> startValues #> <int> -#> 1 0 -#> 2 1 -#> 3 1 +#> 1 NA +#> 2 NA +#> 3 0 #> 4 0 -#> 5 0 -#> 6 0 +#> 5 1 +#> 6 NA #> # ℹ 94 more rows #> # A tibble: 342 × 2 #> from to @@ -347,9 +342,9 @@Examples
#> 5 2 11 #> 6 2 12 #> # ℹ 336 more rows - #manynet::autographr(latticeEg, node_color = "startValues", node_size = 5) - #manynet::autographr(play_segregation(latticeEg, "startValues", 0.5), - # node_color = "startValues", node_size = 5) + # manynet::autographr(latticeEg, node_color = "startValues", node_size = 5) + + # manynet::autographr(play_segregation(latticeEg, "startValues", 0.2), + # node_color = "startValues", node_size = 5)Examples
#> # A tibble: 3 × 4 #> term estimate statistic p.value #> <chr> <dbl> <dbl> <dbl> -#> 1 (intercept) -8.47 -0.839 0.75 -#> 2 alter Citations -0.125 -0.791 0.7 +#> 1 (intercept) -8.47 -0.839 0.6 +#> 2 alter Citations -0.125 -0.791 0.55 #> 3 sim Citations 44.9 3.68 0 glance(model1) #> # A tibble: 1 × 8 diff --git a/reference/tests-1.png b/reference/tests-1.png index 9f6a11d3..2a2f9bd1 100644 Binary files a/reference/tests-1.png and b/reference/tests-1.png differ diff --git a/reference/tests-2.png b/reference/tests-2.png index ef47758c..6ae04c00 100644 Binary files a/reference/tests-2.png and b/reference/tests-2.png differ diff --git a/reference/tests.html b/reference/tests.html index 3a8bbaf6..072dcd9c 100644 --- a/reference/tests.html +++ b/reference/tests.html @@ -18,7 +18,7 @@ @@ -164,8 +164,8 @@Examples
#> QAP Test Results #> #> Observed Value: -0.8571429 -#> Pr(X>=Obs): 0.985 -#> Pr(X<=Obs): 0.08 +#> Pr(X>=Obs): 0.97 +#> Pr(X<=Obs): 0.07 #> plot(qaptest)
diff --git a/sitemap.xml b/sitemap.xml
index d615555f..077f2675 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -60,6 +60,9 @@