The article explores a method called mixed least squares–total least squares (MTLS) for solving linear parameter estimation problems. The researchers analyzed the MTLS problem and found that its condition numbers are related to those of total least squares (TLS) and least squares (LS) problems. They also developed upper bounds for calculating perturbations more efficiently in MTLS. By comparing solutions and residuals of MTLS, TLS, and LS, they discovered interesting connections between these estimation techniques. Numerical experiments were conducted to demonstrate their findings.