search for: abstent

...#> [1] TRUE identical(as(NULL, "vector"), NULL) #> [1] TRUE # supports key vector vector generics length(NULL) #> [1] 0 NULL[c(3, 4, 5)] #> NULL NULL[[1]] #> NULL ``` ## Against ``` r is.vector(NULL) #> [1] FALSE is(NULL, "vector") #> [1] FALSE ``` ## Abstentions ``` r is.atomic(NULL) #> [1] TRUE # documentation states "returns NULL if x is of an atomic type (or NULL)" # is "or" exclusive or inclusive? ``` Hadley -- http://hadley.nz

...ector vector generics > length(NULL) > #> [1] 0 > NULL[c(3, 4, 5)] > #> NULL > NULL[[1]] > #> NULL > ``` > > ## Against > > ``` r > is.vector(NULL) > #> [1] FALSE > > is(NULL, "vector") > #> [1] FALSE > ``` > > ## Abstentions > > ``` r > is.atomic(NULL) > #> [1] TRUE > # documentation states "returns NULL if x is of an atomic type (or NULL)" > # is "or" exclusive or inclusive? > ``` > > Hadley >

...store.item = TRUE, normalize=T, + priors=list(xp=1e-12,xpv=1e-12,bp=1e-12,bpv=1e-12), verbose=T) ideal: analysis of roll call data via Markov chain Monte Carlo methods. Subsetting rollcall object a using dropList Using the following codes to represent roll call votes: Yea: 1 Nay: 0 Abstentions: NA Not In Legislature: 9 Ideal Point Estimation Number of Legislators 30 Number of Items 1172 checking for any user-supplied priors... checking start values... will use eigen-decomposition method to get start values for ideal points...done running 1172 vote-specific probit GLMs for...