Robust means” (or an equivalent phrase) is not intended to add to, or subtract from, the robustness requirements applicable to the particular requirement associated with the phrase, and is used merely as a reminder.
Robust means strong, powerful and able to withstand challenge. For UN peacekeeping operations, robust means “use of all available means”.
Robust here means that qualitative evolution of the system - such as direction of changes and occurrence of events - is not dependent on the choice of parameters, of course, within their plausible range. The CO2 response to the AMOC shutdown is also robust in the model, however, the longer the shutdown, the stronger is an overshoot and the CO2 recovery afterwards. In the CO2 record, it looks like an overshoot and stabilization, like in the Eemian, or as small jump continued by increasing CO2, as in the Holocene (Fig.2 , TI). As the timing of AMOC changes is very sensitive to the freshwater flux, these two types of responses could occur by chance, and therefore are not “robust”.
Examples of Robust in a sentence
If necessary, an independent 3rd party accessibility firm using POUR standards (Perceivable, Operable, Understandable and Robust) may be used to validate the accessibility of the technology.
Robust enumeration of cell subsets from tissue expression profiles.
Robust procedures and a dedicated decontamination room must be in place to minimise the risk of infection transmission to patients, visitors and staff in line with Health Technical Memorandum 01-05: Decontamination in primary care dental practices, (HTM 01-05), published by the Department of Health.
Robust systems were in place to ensure that emergency medicines and equipment do not exceed their expiry date and are immediately available.
Robust relationship inference in genome-wide association studies.
More Definitions of Robust
Robust. ’ monitoring means acquired data are not influenced by other factors. Plant frequency, for example, is not a robust measurement because frequency is influenced by the arrangement of vegetation clumps and by plant size (Whysong & Miller, 1987). Walker (1970) evaluated eight methods of vegetation sampling (including three nonimaging methods for measuring plant cover) and concluded that ‘‘Every method is entirely dependent on the integrity and attitude of the operator’’; also that, ‘‘Human stress is a significant factor in most botanical analyses techniques and may easily invalidate the results obtained.’’ Similar findings and related concerns have been stated by a number of authors (Friedel & Shaw, 1987; NRC, 1994; Donahue, 1999). The human factor is a concern because tradi- tional methods use personal judgement. Attitude, bias, experience, integrity, and stress affect judgement. The human factor affects the ‘‘robustness’’ of many—if not most—nonimaging vegetation sampling methods.
Robust global GDP growth means a year-on-year rate of 2.9 percent in 2016 and 3.3 percent in 2017. These are the latest OECD forecasts. So far the world economy has not succeeded to return to the growth standard of 4.2 percent a year before the financial crisis: on average, advanced countries are lumbering along at a rate of somewhat less than 2 percent, compared to 2.8 percent before 2008, while emerging market and developing economies have slowed from 5.8 to about 4 percent.
Robust means strong, powerful and able to withstand challenge. For UN peacekeeping operations, robust
Robust usually means that the results of forecasting method hardly change even with the small-scale disturbance both in the data and parameters.
Robust means in layman's language. What does it mean
Robust means strong. It does not mean warlike (A), accomplished (C) or competent, timid (D) or fearful, or inexperienced (E).
Robust means that the investment theme is widespread and does not depend overly on implementation choices. To settle this question, we started by computing the daily excess return of ESG indices versus traditional indices by region10 (U.S. and Europe) using MSCI as the data provider, and by provider11 (Euronext and MSCI) in Europe, between 2013 and 2020. We then calculated the rolling 6-month correlation of excess returns between regions (i.e., U.S. vs. Europe) and providers (i.e., Euronext vs. MSCI). Exhibit 5 shows the results, specifically, very low correlation. This points to a lack of robustness.