Hong et al., 2015 - Google Patents
Extremum estimation and numerical derivativesHong et al., 2015
View PDF- Document ID
- 15916026333802266173
- Author
- Hong H
- Mahajan A
- Nekipelov D
- Publication year
- Publication venue
- Journal of Econometrics
External Links
Snippet
Finite-difference approximations are widely used in empirical work to evaluate derivatives of estimated functions. For instance, many standard optimization routines rely on finite- difference formulas for gradient calculations and estimating standard errors. However, the …
- 238000005457 optimization 0 abstract description 21
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
- G06F17/141—Discrete Fourier transforms
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5009—Computer-aided design using simulation
- G06F17/5036—Computer-aided design using simulation for analog modelling, e.g. for circuits, spice programme, direct methods, relaxation methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
- G06F17/30289—Database design, administration or maintenance
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F7/00—Methods or arrangements for processing data by operating upon the order or content of the data handled
- G06F7/38—Methods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation
- G06F7/48—Methods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation using non-contact-making devices, e.g. tube, solid state device; using unspecified devices
- G06F7/544—Methods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation using non-contact-making devices, e.g. tube, solid state device; using unspecified devices for evaluating functions by calculation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2217/00—Indexing scheme relating to computer aided design [CAD]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F1/00—Details of data-processing equipment not covered by groups G06F3/00 - G06F13/00, e.g. cooling, packaging or power supply specially adapted for computer application
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Hong et al. | Extremum estimation and numerical derivatives | |
Chen et al. | Sieve inference on possibly misspecified semi-nonparametric time series models | |
Horowitz | The bootstrap | |
Escanciano et al. | Uniform convergence of weighted sums of non and semiparametric residuals for estimation and testing | |
Fan et al. | Endogeneity in high dimensions | |
Koenker et al. | Unit root quantile autoregression inference | |
Corlay et al. | Functional quantization-based stratified sampling methods | |
Zong et al. | Convergence and stability of the semi-tamed Euler scheme for stochastic differential equations with non-Lipschitz continuous coefficients | |
Liu et al. | A highly efficient and accurate exponential semi-implicit scalar auxiliary variable (ESI-SAV) approach for dissipative system | |
Norets et al. | Adaptive Bayesian estimation of conditional densities | |
CN115359846A (en) | Batch correction method and device for group data, storage medium and electronic equipment | |
You et al. | Interval estimation of the ruin probability in the classical compound Poisson risk model | |
Zhang et al. | Goodness-of-fit test of copula functions for semi-parametric univariate time series models | |
Strauch | Sharp adaptive drift estimation for ergodic diffusions: the multivariate case | |
Mesters et al. | Generalized dynamic panel data models with random effects for cross-section and time | |
Zhang et al. | Adaptive Identification with Guaranteed Performance Under Saturated-Observation and Non-Persistent Excitation | |
Bachoc et al. | Composite likelihood estimation for a Gaussian process under fixed domain asymptotics | |
Xu | Inference of local regression in the presence of nuisance parameters | |
Obuchi et al. | Semi-analytic resampling in lasso | |
Shi et al. | Checking the adequacy of functional linear quantile regression model | |
Han et al. | A sublinear algorithm for barrier-certificate-based data-driven model validation of dynamical systems | |
Peng et al. | Gradient-based simulated maximum likelihood estimation for Lévy-driven Ornstein–Uhlenbeck stochastic volatility models | |
Kressner et al. | Certified and fast computations with shallow covariance kernels | |
Zheng et al. | Numerical methods for SPDEs with tempered stable processes | |
Cline | Stability of nonlinear stochastic recursions with application to nonlinear AR-GARCH models |