Okay I have figured out the issue. I will fix it so it works the way you
expected it to work. Before the fix goes live though it should work to do:
ChisqTest([1,2,3,4],[1,2,2,4], 4)
*note the 4
The issue was when I submitted the code to HypothesisTests.jl the only way
to create a contingency table between two vectors x and y was to also
provide the levels that the categorical variables could take on. Afterwards
I submited a version to StatsBase.jl for ``counts`` that had default
values, but I forgot to update my code at HypothesisTests.jl. Sorry for the
late response!
**Note the above will give you what is equivalent in R to:
> chisq.test(matrix(c(1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,1),nrow = 4,ncol = 4))
Pearson's Chi-squared test
data: matrix(c(1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1), nrow = 4,
ncol = 4)
X-squared = NaN, df = 9, p-value = NA
Warning message:
In chisq.test(matrix(c(1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, :
Chi-squared approximation may be incorrect
However you are probably interested in
> chisq.test(c(1,2,3,4),c(1,2,2,4))
Pearson's Chi-squared test
data: c(1, 2, 3, 4) and c(1, 2, 2, 4)
X-squared = 8, df = 6, p-value = 0.2381
When I wrote up the function there wasn't a good equivalent of R's
``table`` function. I will try to flesh out this code so it works closer to
R. In the meantime the best thing is to work with the full contingency
table i.e.:
julia> ChisqTest([1 0 0; 0 1 0; 0 1 0; 0 0 1])
Pearson's Chi-square Test
-------------------------
Population details:
parameter of interest: Multinomial Probabilities
value under h_0:
[0.0625,0.0625,0.0625,0.0625,0.125,0.125,0.125,0.125,0.0625,0.0625,0.0625,0.0625]
point estimate: [0.25,0.0,0.0,0.0,0.0,0.25,0.25,0.0,0.0,0.0,0.0,0.25]
95% confidence interval:
[(0.0,1.0),(0.0,1.0),(0.0,1.0),(0.0,1.0),(0.0,1.0),(0.0,1.0),(0.0,1.0),(0.0,1.0),(0.0,1.0),(0.0,1.0),(0.0,1.0),(0.0,1.0)]
Test summary:
outcome with 95% confidence: fail to reject h_0
two-sided p-value: 0.23810330555354436 (not significant)
Details:
Sample size: 4
statistic: 8.0
degrees of freedom: 6
residuals:
[1.5,-0.5,-0.5,-0.5,-0.7071067811865475,0.7071067811865475,0.7071067811865475,-0.7071067811865475,-0.5,-0.5,-0.5,1.5]
std. residuals:
[2.0,-0.6666666666666666,-0.6666666666666666,-0.6666666666666666,-1.1547005383792517,1.1547005383792517,1.1547005383792517,-1.1547005383792517,-0.6666666666666666,-0.666666
6666666666,-0.6666666666666666,2.0]
