I want to do the following with some time series data:
Calculate 95% confidence interval for mean defined as +/-sigma(x)qt(0.025,
N*-1) / sqrt(N*) where sigma(x) is the standard deviation at any point x
and qt(0.025, N*-1) is the 2.5 percentage point of the Student-t
distribution with N*-1 degrees of freedom.
I have been trying to do this with HypothesisTests' ci() and
OneSampleTTest() functions, but as far as I can see OneSampleTTest() does
not allow me to choose the number of degrees of freedom.
julia> t = OneSampleTTest(arr)
One sample t-test
-----------------
Population details:
parameter of interest: Mean
value under h_0: 0
point estimate: 0.3835
95% confidence interval: (0.14217301685460967,0.6248269831453903)
Test summary:
outcome with 95% confidence: reject h_0
two-sided p-value: 0.0057946078675091515 (very significant)
Details:
number of observations: 10
t-statistic: 3.5948622927526235
degrees of freedom: 9
empirical standard error: 0.10668002520517972
julia> t.df
9
julia> ci(t, 0.025, tail=:both)
(0.09706297518543938,0.6699370248145606)
Can anybody point me in the right direction?
