Question

We use the statistical set-up from a previous problem. Recall that X_1, \ldots , X_ n are i.i.d. samples with cdf F, and F^0 denotes the cdf of \textsf{Unif}([0,1]). We have the null and alternative hypotheses

\displaystyle H_0 \displaystyle : F(t) = F^0
\displaystyle H_1 \displaystyle : F(t) \neq F^0.
In the last problem, we computed the value of the test-statistic

T_ n = \sqrt{n} \max _{i = 1, \ldots , n} \left\{ \max \left(\bigg| \frac{i -1}{n} - X_{(i)} \mathbf{1}\left( X_{(i)} \in [0,1]\right) \bigg|, \bigg| \frac{i }{n} - X_{(i)} \mathbf{1}\left( X_{(i)} \in [0,1]\right) \bigg|\right) \right\} .

for the data set

\mathbf{x}= 0.8, 0.7, 0.4, 0.7, 0.2.

You will use the Kolmogorov-Smirnov test

\psi _5 = \mathbf{1}( T_5 > C ).

What value of C should be chosen so that \psi _5 has (non-asymptotic) level 5 \%?

Note: Refer to the table in the slide “K-S table". If you are using this table, also note that the quantiles are presented for the statistic \sup _ t |F_ n(t) - F(t)| and you need to account for the factor \sqrt{n} while entering the quantile value for your answer. That is, the number x in the n-th row of the column labeled by the level \alpha table in the slide “K-S table" is such that

P_ n^{KS}\left(\frac{T_ n}{\sqrt{n}} > x \right) = \alpha .

unanswered
For the Kolmogorov-Smirnov test of level 5\%, would you reject or fail to reject the null hypothesis on the above data set?



Reject

Fail to reject

Answers

There are no human answers yet.
Answered by GPT 3.5
To determine the value of C that should be chosen so that ψ5 has a non-asymptotic level of 5%, we need to calculate the critical value from the Kolmogorov-Smirnov (KS) table.

First, let's calculate the test statistic Tn using the given data:

x = 0.8, 0.7, 0.4, 0.7, 0.2

Tn = √(n) * max(i = 1,...,n) [ max (| (i-1)/n - X(i) * 1(X(i)∈[0,1]) |, | i/n - X(i) * 1(X(i)∈[0,1]) | ) ]

For n = 5, we have:

T5 = √(5) * max [ max (| (1-1)/5 - 0.2 * 1(0.2∈[0,1]) |, | 1/5 - 0.2 * 1(0.2∈[0,1]) | ),
max (| (2-1)/5 - 0.4 * 1(0.4∈[0,1]) |, | 2/5 - 0.4 * 1(0.4∈[0,1]) | ),
max (| (3-1)/5 - 0.7 * 1(0.7∈[0,1]) |, | 3/5 - 0.7 * 1(0.7∈[0,1]) | ),
max (| (4-1)/5 - 0.7 * 1(0.7∈[0,1]) |, | 4/5 - 0.7 * 1(0.7∈[0,1]) | ),
max (| (5-1)/5 - 0.8 * 1(0.8∈[0,1]) |, | 5/5 - 0.8 * 1(0.8∈[0,1]) | ) ]

Calculating each term inside the max, we get:

T5 = √(5) * max [ max (| 0 - 0.2 |, | 0.2 - 0.2 | ),
max (| 0.2 - 0.4 |, | 0.4 - 0.4 | ),
max (| 0.4 - 0.7 |, | 0.6 - 0.7 | ),
max (| 0.6 - 0.7 |, | 0.8 - 0.7 | ),
max (| 0.8 - 0.8 |, | 1 - 0.8 | ) ]

Calculating further, we get:

T5 = √(5) * max [ 0.2, 0.2,
0.2, 0.4,
0.3, 0.2,
0.1, 0.1,
0, 0.2 ]

Taking the maximum of each pair, we get:

T5 = √(5) * max [ 0.2, 0.4, 0.3, 0.1, 0.2 ] = √(5) * 0.4 ≈ 0.895

Now, using the KS table, we need to find the value of x such that:

Pn^(KS) (Tn/√(n) > x) = 0.05 (since we want a level of 5%)

From the table, we find that for a level of 5% and n = 5, the corresponding value of x is approximately 1.036.

Since T5/√(5) = 0.895/√(5) ≈ 0.4 < 1.036, we fail to reject the null hypothesis (H0) at the 5% level.

Therefore, the answer is: Fail to reject.

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