Greetings, I want to compare the performance of two samplers, A and B. The samplers both take different numbers of samples and are evaluated by linearly interpolating between the sample points.
For example, if we sample at time t, and record 10, at time t+2, and record 20, this implies a value of 15 at t+1. If the actual value at t+1 was 17, the error at t+1 is 2. The sum of squared errors is calculated for each sampler (over time period t=1 to t=n) along with the number of samples taken. Thus, if A samples n_a times, SSE for A is based on (n - n_a) error measurements. Similarly, if B samples n_b times SSE for B is based on (n - n_b) error measurements. Can I use a simple comparison of variances to compare A and B? If so, what exactly is the formula I should use, and what distribution can I compare the result to in order to determine whether there is a significant difference between them? Thanks in advance, Don . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
