Statistical inference for complex equations was studied using maximum likelihood estimation. The researchers derived formulas for tests commonly used in this context and calculated the power of statistical tests in two important situations. They refined existing theory to ensure accurate results and showed that uniform convergence can be achieved if certain conditions are met. The study provides valuable insights for designing experiments and interpreting data in nonlinear statistical analysis.