The weight effects were calculated using weff = n ∑ w i 2 (∑ w i ) 2 where: n denotes sample size and w denotes weights [ 20- 22].
However, sample size was calculated using the formula for single proportion: N = ZP Q/ E [ 14] Where: N denotes sample size, Z denotes standard normal deviation, a constant set at the 95%% confidence interval, which is 1.96 and P denotes proportion of women who have ever screened for cervical cancer which is 15%% [ 15].
Implementing these large-p-with-small-n regressions (where n denotes sample size and p represents the number of predictors) poses several statistical and computational challenges, including how to confront the so-called "curse of dimensionality" (Bellman 1961) as well as the complexity of a genetic mechanism that can involve various types and orders of interactions.
Assuming N r and N a denote sample size of range and azimuth dimension signal, respectively, then the matrix of SAR echo signals can be written as S = s 1, 1, s 1, 2, …, s 1, N r ; s 2, 1, s 2, 2, …, s 2, N r ; … ; s N a, 1, s N a, 2, …, s N a, N r (3).
Numbers above bars denote sample size.
The score confidence limits used are given by where ^ p denotes the sample proportion, n denotes the sample size, and zα/2 denotes the 1 – α/2 quantile of the standard normal distribution (8 ); α was set to 0.05 to obtain 95% confidence limits.
Let X be a T× p matrix, where T denotes the sample size and p denotes the number of explanatory variables.
The consistency rate of an M-estimator r̂n for the change-point parameter r is shown to be n while it is n1/2 for the coefficient parameter estimators, where n denotes the sample size.
21 The default coarsening algorithm by the matching software is the Scott break method: ε scott = 3.5 s ̄ n 2 n - 1 / 3, where n denotes the sample size and s ̄ n 2 the sample standard deviation (Scott 1992).
Figure 2, illustrates the correlation between ranking lists by utilizing the Spearman rank correlation coefficient obtained by employing Equation (23), the Spearman rank correlation coefficient similarity of the rankings in Table 9. {r}_s=1-frac{sum limits_{i=1}^n{D}{nlefteft({n}^2-1right)}, (23 where D is differences between the two ranks and n denotes the sample size.
