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A robust parameter design, introduced by Genichi Taguchi, is an experimental design used to exploit the interaction between control and uncontrollable
Robust_parameter_design
Design of tasks
of scientific experiment Research design – Overall strategy utilized to carry out research Robust parameter design Sample size determination – Statistical
Design_of_experiments
Software Package
screening, characterization, optimization, robust parameter design, mixture designs and combined designs. Design–Expert provides test matrices for screening
Design–Expert
Approach to controller design that explicitly deals with uncertainty
in the design. The ability of a feedback control system to maintain stability and performance under uncertainty is referred to as robustness. The term
Robust_control
Type of statistics
distributions. Robust estimates have been studied for the following problems: estimating location parameters estimating scale parameters estimating regression
Robust_statistics
Topics referred to by the same term
demonstration, a technique to teach new skills to robots Robust parameter design, a technique for design of processes and experiments RPD machine gun, a Soviet
RPD
Statistical methods to improve the quality of manufactured goods
methods (Japanese: タグチメソッド) are statistical methods, sometimes called robust design methods, developed by Genichi Taguchi to improve the quality of manufactured
Taguchi_methods
Ability of a system to resist change without adapting its initial stable configuration
uncertain parameters are known, the probability of instability can be estimated, leading to the concept of stochastic robustness. "Robustness in the small"
Robustness
American statistician
and jackknife, and industrial statistics, including design of experiments, and robust parameter design (Taguchi methods). Born in Taiwan, Wu earned a B.S
C._F._Jeff_Wu
Regulation of nonlinear systems
often designed at various operating points using linearized models of the system dynamics and are scheduled as a function of a parameter or parameters for
Linear parameter-varying control
Linear_parameter-varying_control
Computer optimization software
problem is robust design of the product parameters in the early design process (Robust Parameter Design (RPD)). Thereby, optimal product parameters should
OptiY
Experimental design that is optimal with respect to some statistical criterion
statistician Kirstine Smith. In the design of experiments for estimating statistical models, optimal designs allow parameters to be estimated without bias and
Optimal_experimental_design
Specialized form of regression analysis, in statistics
misleading results otherwise (i.e. are not robust to assumption violations). Robust regression methods are designed to limit the effect that violations of
Robust_regression
Iterative decision analytic framework
large degree of uncertainty. One source of the name "robust decision" was the field of robust design popularized primarily by Genichi Taguchi in the 1980s
Robust_decision-making
Method used in finance to determine the optimal parameters for a trading strategy
used in finance to determine the optimal parameters for a trading strategy and to determine the robustness of the strategy. Walk Forward Analysis was
Walk_forward_optimization
Parameter controlling the machine learning process
involves storing and organizing the parameters and results, and making sure they are reproducible. In the absence of a robust infrastructure for this purpose
Hyperparameter (machine learning)
Hyperparameter_(machine_learning)
Type of sensitivity analysis
about a real-valued parameter. Scandinavian Journal of Statistics 24:463-483. Moreno, E., and L.R. Pericchi (1993). Bayesian robustness for hierarchical
Robust_Bayesian_analysis
Kind of numerical parameter of a parametric family of probability distributions
probability theory and statistics, a shape parameter (also known as form parameter) is a kind of numerical parameter of a parametric family of probability
Shape_parameter
Machine learning technique
domain adaptation. These contain far fewer parameters than the original model and can be fine-tuned in a parameter-efficient way by tuning only their weights
Fine-tuning_(deep_learning)
Function of observations and unobservable parameters
of robust statistics, pivotal quantities are robust to changes in the parameters — indeed, independent of the parameters — but not in general robust to
Pivotal_quantity
Concept in statistics
1971.10482258. S2CID 120949417. Huber, Peter J. (1992). "Robust Estimation of a Location Parameter". Breakthroughs in Statistics. Springer Series in Statistics
Location_parameter
Statistical measure of variability
referred to as the median absolute deviation from the median (MADFM), is a robust or outlier-resistant measure of the variability of a univariate sample of
Median_absolute_deviation
Statistical measure
a scale parameter is a special kind of numerical parameter of a parametric family of probability distributions. The larger the scale parameter, the more
Scale_parameter
Tools for modelling chip fabrication
contains: A primitive device library Symbols Device parameters PCells Verification checks Design rule checking Layout versus schematic Antenna and electrical
Process_design_kit
Japanese statistician
that they are insensitive ("robust") to parameters outside the design engineer's control. Innovations in the statistical design of experiments, notably the
Genichi_Taguchi
Advanced method of process control
Santos, Lino O.; Alonso, Antonio A. (2012). "A Robust Multi-Model Predictive Controller for Distributed Parameter Systems" (PDF). Journal of Process Control
Model_predictive_control
also the evaluation of robustness, i.e. the sensitivity towards scatter of design variables or random fluctuations of parameters. In 2019, Dynardo GmbH
OptiSLang
Type of control method
different from robust control in that it does not need a priori information about the bounds on these uncertain or time-varying parameters; robust control guarantees
Adaptive_control
related methods to new technology and product development process - Robust parameter design (RPD) ISO/IEC 16350:2015 Information technology - Systems and software
List of ISO standards 16000–17999
List_of_ISO_standards_16000–17999
Quality measure of a statistical method
class of estimators motivated by these concerns. They can be designed to yield both robustness and high relative efficiency, though possibly lower efficiency
Efficiency_(statistics)
Mathematical optimization theory
Fernando P.; Saraiva, Pedro M. (1998). "Robust optimization framework for process parameter and tolerance design". AIChE Journal. 44 (9): 2007–2017. Bibcode:1998AIChE
Robust_optimization
Quality assurance testing to determine the robustness of software
Robustness testing is any quality assurance methodology focused on testing the robustness of software. Robustness testing has also been used to describe
Robustness_testing
Robustification as it is defined here is sometimes referred to as parameter design or robust parameter design (RPD) and is often associated with Taguchi methods. Within
Robustification
Quantity that indexes a parametrized family of probability distributions
In statistics, as opposed to its general use in mathematics, a parameter is any quantity of a statistical population that summarizes or describes an aspect
Statistical_parameter
Mathematical optimization approach to deal with optimization problems under uncertainty
optimality robustness; Feasibility robustness means that the solution should remain feasible for (almost) all possible values of uncertain parameters and flexibility
Robust_fuzzy_programming
is to verify that the design is robust enough to provide operation which meets the system performance specification over design life under worst-case
Worst-case_circuit_analysis
Statistical estimator
supremum risk. Robust optimization is an approach to solve optimization problems under uncertainty in the knowledge of underlying parameters. For instance
Minimax_estimator
Approach to optimizing robustness to failure
models are designed for the analysis of small perturbations in a given nominal value of a parameter, Sniedovich argues that info-gap's robustness model is
Info-gap_decision_theory
fidelity (low-, middle-, high fidelity models); IOSO RM: Robust design optimization and robust optimal control software; IOSO NM is used to maximize or
IOSO
Function related to statistics and probability theory
compared are parameterized by a parameter, with the parameter often written as θ, or they are parameterized by multiple parameters given as the components of
Likelihood_function
Range to estimate an unknown parameter
contain (in repeated sampling) the true value of an unknown statistical parameter, such as a population mean. Rather than reporting a single point estimate
Confidence_interval
k.a. braces, a.k.a. curly brackets Semicolon (;) statement terminator Parameter list delimited by parentheses (()) Infix notation for arithmetical and
List of C-family programming languages
List_of_C-family_programming_languages
Overview of and topical guide to statistics
Ancillary statistic Minimal sufficiency Kullback–Leibler divergence Nuisance parameter Order statistic Bayesian inference Bayes' theorem Bayes estimator Prior
Outline_of_statistics
communication system, the link margin (LKM) is a critical parameter that measures the reliability and robustness of the communication link. It is expressed in decibels
Link_margin
Marker covertly embedded in a signal
general, it is easy to create either robust watermarks or imperceptible watermarks, but the creation of both robust and imperceptible watermarks has proven
Digital_watermarking
Persistence of a biological trait under uncertain conditions
In evolutionary biology, robustness of a biological system (also called biological or genetic robustness) is the persistence of a certain characteristic
Robustness_(evolution)
Statistical modeling method
and are not assigned following a study design. A large number of procedures have been developed for parameter estimation and inference in linear regression
Linear_regression
Branch of engineering and mathematics
process control. Robust control deals explicitly with uncertainty in its approach to controller design. Controllers designed using robust control methods
Control_theory
technique utilising the Nichols chart (NC) in order to achieve a desired robust design over a specified region of plant uncertainty. Desired time-domain responses
Quantitative_feedback_theory
Discipline within engineering design
of input variables and parameters. This second approach is sometimes referred to as robustification, parameter design or design for six sigma. Though the
Probabilistic_design
Statistical method
uses deprecated parameter |citeseerx= (help) de la Cuesta, B; Imai, K (2016). "Misunderstandings About the Regression Discontinuity Design in the Study of
Regression discontinuity design
Regression_discontinuity_design
Statistical method for fitting a line
In non-parametric statistics, the Theil–Sen estimator is a method for robustly fitting a line to sample points in the plane (a form of simple linear regression)
Theil–Sen_estimator
Moving average and polynomial regression method for smoothing data
(\cdot )} is a robustness function and s {\displaystyle s} is a scale parameter. Discussion of the merits of different choices of robustness function is
Local_regression
Software quality metric
resilience to change, supporting the design of maintainable and robust systems. Practical Guide to Structured Systems Design. ISBN 978-0136907695. Fundamentals
Connascence
direct way of design which must be followed by a sensitivity analysis and robustness of parameters. However, determining design parameters from an availability
Design_for_availability
Process of finding a spatial transformation that aligns two point clouds
introducing a control parameter β > 0 {\displaystyle \beta >0} . In the deterministic annealing method, the control parameter β {\displaystyle \beta
Point-set_registration
Measure of how a closed loop transfer function is affected by parameter changes
J. Astrom, "Model uncertainty and robust control," in Lecture Notes on Iterative Identification and Control Design. Lund, Sweden: Lund Institute of Technology
Sensitivity_(control_systems)
Measure of statistical effect size
proposed statistical parameter, strictly standardized mean difference (SSMD), can address these issues. One estimate of SSMD is robust to outliers. high-throughput
Z-factor
Sampling methodology in statistics
modifying the estimated parameter, cluster sampling is unbiased when the clusters are approximately the same size. In this case, the parameter is computed by combining
Cluster_sampling
the system matrices has dependence on a parameter, such as robust control problems and control of linear-parameter varying systems. This approach has recently
Finsler's_lemma
Statistical measure used in survey research
measure of the expected impact of a sampling design on the variance of an estimator for some parameter of a population. It is calculated as the ratio
Design_effect
Class of statistical estimators
parameter estimation. Springer Series in Statistics. New York: Springer. doi:10.1007/b98823. ISBN 978-0-387-98225-0. Huber, Peter J. (2009). Robust Statistics
M-estimator
Chart of a transfer function's phase response vs. magnitude
(QFT) of Horowitz and Sidi, which is a well known method for robust control system design. In most cases, arg ( G ( s ) ) {\displaystyle \arg(G(s))}
Nichols_plot
Observation that would cause a large change if deleted
influential observation is one whose deletion has a large effect on the parameter estimates. Various methods have been proposed for measuring influence
Influential_observation
Robust and nonparametric estimator of a population's location parameter
statistics, the Hodges–Lehmann estimator is a robust and nonparametric estimator of a population's location parameter. For populations that are symmetric about
Hodges–Lehmann_estimator
Statistical property
loss functions are used in statistics, particularly in robust statistics. For univariate parameters, median-unbiased estimators remain median-unbiased under
Bias_of_an_estimator
Statistical indicators in signal processing
Hjorth parameters are indicators of statistical properties used in signal processing in the time domain introduced by Bo Hjorth in 1970. The parameters are
Hjorth_parameters
Lebanese-Greek-American mathematician
then open problem on robust stability and performance problems for constant real parameter uncertainty in the literature via parameter-dependent Lyapunov
Wassim_Michael_Haddad
Iterative simulation method
optima. However, APSO will introduce new algorithm parameters, it does not introduce additional design or implementation complexity nonetheless. Besides
Particle_swarm_optimization
Variations of semiconductor layouts based on variations of fabrication processes
example of a design-of-experiments (DoE) technique that refers to a variation of fabrication parameters used in applying an integrated circuit design to a semiconductor
Process_corners
in which a design response of interest is influenced by several design parameters. DOE methods in combination with RSM can predict design response values
Optimus_platform
Single measure of some attribute of a sample
mean square error, low variance, robustness, and computational convenience. Information of a statistic on model parameters can be defined in several ways
Statistic
Class of statistical models
least squares method for maximum likelihood estimation (MLE) of the model parameters. MLE remains popular and is the default method on many statistical computing
Generalized_linear_model
Format defined in the H.264/AVC and HEVC video coding standards
characteristic formatting and loss/error robustness requirements. The H.264/AVC and HEVC standards are designed for technical solutions including areas
Network_Abstraction_Layer
Statistical experimental design approach
Standards and Technology) Robust parameter designs Box, G.E.; Hunter, J.S.; Hunter, W.G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery
Fractional_factorial_design
Worst-case distance (WCD) is a robustness metric used in electronic design for yield optimization and design centering. The metric quantifies how well
Worst-case_distance
decision optimal design outlier p-value pairwise independence A set of random variables, any two of which are independent. parameter Any measured quantity
Glossary of probability and statistics
Glossary_of_probability_and_statistics
Middle quantile of a data set or probability distribution
in robust statistics. The theory of median-unbiased estimators was revived by George W. Brown in 1947: An estimate of a one-dimensional parameter θ will
Median
Type of experimental design
appears in the plan matrix, creating a 557 runs design with values, −1, 0, +1, to estimate the 496 parameters of a full quadratic model. Adding axial points
Plackett–Burman_design
Degree of interdependence between software modules
locality, degree, and resilience to change, supporting the design of maintainable and robust systems. Coupling in Software Engineering describes a version
Coupling (computer programming)
Coupling_(computer_programming)
Business management method
defining customer needs and leads to the development of robust processes to deliver those needs. Design for Six Sigma emerged from the Six Sigma and the
Design_for_Six_Sigma
often used to dynamically modify operational system parameters to maximize efficiency and robustness. Examples of self-tuning systems in computing include:
Self-tuning
system. There are explicit relations between the performance parameters specified before the design and the coefficients of the controller polynomials as described
Coefficient_diagram_method
Method of data analysis
Robust Principal Component Analysis (RPCA) is a modification of the widely used statistical procedure of principal component analysis (PCA) which works
Robust principal component analysis
Robust_principal_component_analysis
Experimental design framework
prior knowledge on the parameters to be determined as well as uncertainties in observations. The theory of Bayesian experimental design is to a certain extent
Bayesian_experimental_design
tracking error during the pth repetition and K {\displaystyle K} is a design parameter representing operations on e p {\displaystyle e_{p}} . Achieving perfect
Iterative_learning_control
Experimental design in statistical mathematics
instance, in a study, a central composite design was employed to investigate the effect of critical parameters of organosolv pretreatment of rice straw
Central_composite_design
In the design of experiments, completely randomized designs are for studying the effects of one primary factor without the need to take other nuisance
Completely_randomized_design
Theorem in mathematics and economics
mechanism design analysis mainly based on the envelope theorem and other familiar techniques and concepts in demand theory. For a multidimensional parameter space
Envelope_theorem
Concept in medicine referring to design of clinical trials
In an adaptive design of a clinical trial, the parameters and conduct of the trial for a candidate drug or vaccine may be changed based on an interim analysis
Adaptive_design_(medicine)
Numerical optimization method
parameter searching space, e.g. a confounded design with exponentially distributed spacings/steps. This search goes on sequentially on each parameter
Random_search
International aeronautics software standard
additional code, that cannot be traced to Source Code, is achieved." Parameter Data Item Files - Provides separate information that influences the behavior
DO-178C
Collection of statistical models
Theory of the Design of Experiments. doi:10.1201/9781420035834. ISBN 978-0-429-12628-4. Hettmansperger, T. P.; McKean, J. W. (1998). Robust nonparametric
Analysis_of_variance
analysis Robbins lemma Robust Bayesian analysis Robust confidence intervals Robust measures of scale Robust regression Robust statistics Root mean square
List_of_statistics_articles
Engineering consultancy
sampling, or FORM. Robustness studies can tell the user how sensitive the design is to stochastic variation of the input parameters. Reliability studies
Red_Cedar_Technology
Poisson type distributions. The Conway–Maxwell–Poisson distribution, a two-parameter extension of the Poisson distribution with an adjustable rate of decay
List of probability distributions
List_of_probability_distributions
Terms used in experimental design
experimental research and relevant to the fields of statistics, experimental design, and estimation theory. Alias: When the estimate of an effect also includes
Glossary of experimental design
Glossary_of_experimental_design
early as in the late 1970s by Mercer and Sampson for finding optimal parameter settings of a genetic algorithm. Meta-optimization and related concepts
Meta-optimization
Experimental designs for response surface methodology
central composite design (CCD) and Doehlert design, despite its poor coverage of the corner of nonlinear design space. The design with 7 factors was
Box–Behnken_design
Mathematical relation assigning a probability event to a cost
hierarchy[clarification needed]. In statistics, typically a loss function is used for parameter estimation, and the event in question is some function of the difference
Loss_function
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ROBUST PARAMETER-DESIGN
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