The phrase "are very robust to changes" is correct and usable in written English.
It can be used when discussing the resilience or adaptability of a system, process, or model in the face of variations or modifications.
Example: "The new software algorithms are very robust to changes in user behavior, ensuring consistent performance."
Alternatives: "are highly resilient to changes" or "are quite adaptable to changes."
It should be noted that the final results of GRA for MADM problems are very robust to changes in the values of (rho ).
Finally, we showed that the estimates of the long-term FPR based on data from a longitudinal HIV surveillance are very robust to changes in the definition of "long-term" (i.e. the choice of the maximum BED progression time).
The results are very robust to changes in the length of the test data, which can be equated to changes in the cutoff criteria used during microarray analysis.
Sensitivity analyses demonstrated that the conclusions are very robust to changes in the assumptions and methods used to measure costs and utilities and conduct the analysis (figure 3).
The present article illustrates that cogeneration systems can be very robust to changes.
The shape of the curves was very robust to changes in the number of knots in the regression splines or the smoother span in the lowess algorithm.
Similar to the issue of cost function sensitivity discussed above, the principle of how to optimize exposure assessment seem, however, to be very robust to changes in unit costs and variance components when between-subject variability is large compared to within-subject variability and subject recruitment costs are small or similar to costs for setting up measurement occasions (table 2).
Altogether our study results are very robust to model changes.
Our models show that oscillations are very robust to parameter changes when we assume that the mechanism for p53 stabilization is via ARF.
Numerical experiments show that the coefficients are very robust to underestimation of τ and robust to overestimation.
Thus, our gene cluster construction algorithm was very robust to criteria changes.
