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Products related to Estimation:


  • Mineral Resource Estimation
    Mineral Resource Estimation

    Mineral resource estimation has changed considerably in the past 25 years: geostatistical techniques have become commonplace and continue to evolve; computational horsepower has revolutionized all facets of numerical modeling; mining and processing operations are often larger; and uncertainty quantification is becoming standard practice.Recent books focus on historical methods or details of geostatistical theory.So there is a growing need to collect and synthesize the practice of modern mineral resource estimation into a book for undergraduate students, beginning graduate students, and young geologists and engineers.It is especially fruitful that this book is written by authors with years of relevant experience performing mineral resource estimation and with years of relevant teaching experience.This comprehensive textbook and reference fills this need.

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  • Bayesian Estimation of DSGE Models
    Bayesian Estimation of DSGE Models

    Dynamic stochastic general equilibrium (DSGE) models have become one of the workhorses of modern macroeconomics and are extensively used for academic research as well as forecasting and policy analysis at central banks.This book introduces readers to state-of-the-art computational techniques used in the Bayesian analysis of DSGE models.The book covers Markov chain Monte Carlo techniques for linearized DSGE models, novel sequential Monte Carlo methods that can be used for parameter inference, and the estimation of nonlinear DSGE models based on particle filter approximations of the likelihood function.The theoretical foundations of the algorithms are discussed in depth, and detailed empirical applications and numerical illustrations are provided.The book also gives invaluable advice on how to tailor these algorithms to specific applications and assess the accuracy and reliability of the computations. Bayesian Estimation of DSGE Models is essential reading for graduate students, academic researchers, and practitioners at policy institutions.

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  • Small Area Estimation and Microsimulation Modeling
    Small Area Estimation and Microsimulation Modeling

    Small Area Estimation and Microsimulation Modeling is the first practical handbook that comprehensively presents modern statistical SAE methods in the framework of ultramodern spatial microsimulation modeling while providing the novel approach of creating synthetic spatial microdata.Along with describing the necessary theories and their advantages and limitations, the authors illustrate the practical application of the techniques to a large number of substantive problems, including how to build up models, organize and link data, create synthetic microdata, conduct analyses, yield informative tables and graphs, and evaluate how the findings effectively support the decision making processes in government and non-government organizations. FeaturesCovers both theoretical and applied aspects for real-world comparative research and regional statistics productionThoroughly explains how microsimulation modeling technology can be constructed using available datasets for reliable small area statisticsProvides SAS codes that allow readers to utilize these latest technologies in their own work. This book is designed for advanced graduate students, academics, professionals and applied practitioners who are generally interested in small area estimation and/or microsimulation modeling and dealing with vital issues in social and behavioural sciences, applied economics and policy analysis, government and/or social statistics, health sciences, business, psychology, environmental and agriculture modeling, computational statistics and data simulation, spatial statistics, transport and urban planning, and geospatial modeling.

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  • Cyber-Physical Power Systems State Estimation
    Cyber-Physical Power Systems State Estimation

    Cyber-Physical Power System State Estimation updates classic state estimation tools to enable real-time operations and optimize reliability in modern electric power systems.The work introduces and contextualizes the core concepts and classic approaches to state estimation modeling.It builds on these classic approaches with a suite of data-driven models and non-synchronized measurement tools to reflect current measurement trends required by increasingly more sophisticated grids.Chapters outline core definitions, concepts and the network analysis procedures involved in the real-time operation of EPS. Specific sections introduce power flow problem in EPS, highlighting network component modeling and power flow equations for state estimation before addressing quasi static state estimation in electrical power systems using Weighted Least Squares (WLS) classical and alternatives formulations.Particularities of the state estimation process in distribution systems are also considered.Finally, the work goes on to address observability analysis, measurement redundancy and the processing of gross errors through the analysis of WLS static state estimator residuals.

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  • What is the biggest error estimation?

    The biggest error estimation occurs when there is a lack of understanding or consideration of the underlying assumptions and limitations of the estimation method being used. This can lead to overconfidence in the accuracy of the estimation and result in significant errors in decision-making. It is important to critically evaluate the assumptions and uncertainties associated with any estimation in order to minimize the potential for large errors.

  • In your estimation, what is your IQ?

    As an AI language model, I do not have personal experiences, emotions, or a sense of self, so I do not have an IQ. My purpose is to provide information and assist with tasks to the best of my ability based on the input I receive. If you have any questions or need assistance with something, feel free to ask!

  • Which estimation questions are suitable for children?

    Estimation questions that involve familiar objects or activities are suitable for children. For example, asking children to estimate the number of toys in a box, the length of a piece of string, or the amount of time it takes to walk to a certain location are all appropriate for their age and understanding. Additionally, estimation questions that relate to their daily routines, such as estimating the number of cookies in a jar or the number of minutes it takes to brush their teeth, are also suitable for children. These types of questions allow children to practice their estimation skills in a context that is relevant and relatable to them.

  • What is an estimation function in statistics?

    An estimation function in statistics is a mathematical formula or algorithm used to estimate a population parameter based on sample data. It takes the sample data as input and produces an estimate of the population parameter as output. Estimation functions are used to make inferences about the population based on the information contained in the sample. They are essential tools in statistical analysis for making predictions and drawing conclusions about the population from limited sample data.

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  • Reserves Estimation for Geopressured Gas Reservoirs
    Reserves Estimation for Geopressured Gas Reservoirs

    Reserves Estimation for Geopressured Gas Reservoirs aims to introduce the principles and methods for calculating reserves of geopressured gas reservoirs with the material balance method, presenting advantages, disadvantages and applicable conditions of various methods.The book, based on manual analysis, explains methods and calculation steps with more than 30 gas reservoir examples.It will help gas reservoir engineers learn basic principles and calculation methods and familiarize themselves with the content of the software Black Box, which in turn helps improve the level of gas field performance analysis and the level of gas field development.

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  • Software Estimation : Demystifying the Black Art
    Software Estimation : Demystifying the Black Art

    Often referred to as the “black art” because of its complexity and uncertainty, software estimation is not as difficult or puzzling as people think.In fact, generating accurate estimates is straightforward—once you understand the art of creating them.In his highly anticipated book, acclaimed author Steve McConnell unravels the mystery to successful software estimation—distilling academic information and real-world experience into a practical guide for working software professionals.Instead of arcane treatises and rigid modeling techniques, this guide highlights a proven set of procedures, understandable formulas, and heuristics that individuals and development teams can apply to their projects to help achieve estimation proficiency. Discover how to: Estimate schedule and cost—or estimate the functionality that can be delivered within a given time frame Avoid common software estimation mistakes Learn estimation techniques for you, your team, and your organization * Estimate specific project activities—including development, management, and defect correction Apply estimation approaches to any type of project—small or large, agile or traditional Navigate the shark-infested political waters that surround project estimates When many corporate software projects are failing, McConnell shows you what works for successful software estimation.

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  • Estimation of the Time Since Death
    Estimation of the Time Since Death

    Estimation of the Time Since Death remains the foremost authoritative book on scientifically calculating the estimated time of death postmortem.Building on the success of previous editions which covered both the early and later postmortem periods this edition includes a new chapter on DNA/RNA degradation and further new content on drug testing in hair, thus widening the scope of the material.Chapters have been improved, updated and expanded, and include new and additional images to enhance the text.A unique work of synthesis combining rigorous science with practical guidance, this update reinforces the book’s reputation as an invaluable resource – and also the standard – for the estimation of the time since death.

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  • Quantized Compressive Sampling for Structured Signal Estimation
    Quantized Compressive Sampling for Structured Signal Estimation

    This thesis investigates different approaches to enable the use of compressed sensing (CS)-based acquisition devices in resource-constrained environments relying on cheap, energy-efficient sensors.We consider the acquisition of structured low-complexity signals from excessively quantized 1-bit observations, as well as partial compressive measurements collected by one or multiple sensors.In both scenarios, the central goal is to alleviate the complexity of sensing devices in order to enable signal acquisition by simple, inexpensive sensors. In the first part of the thesis, we address the reconstruction of signals with a sparse Fourier transform from 1-bit time domain measurements.We propose a modification of the binary iterative hard thresholding algorithm, which accounts for the conjugate symmetric structure of the underlying signal space.In this context, a modification of the hard thresholding operator is developed, whose use extends to various other (quantized) CS recovery algorithms.In addition to undersampled measurements, we also consider oversampled signal representations, in which case the measurement operator is deterministic rather than constructed randomly.Numerical experiments verify the correct behavior of the proposed methods. The remainder of the thesis focuses on the reconstruction of group-sparse signals, a signal class in which nonzero components are assumed to appear in nonoverlapping coefficient groups.We first focus on 1-bit quantized Gaussian observations and derive theoretical guarantees for several reconstruction schemes to recover target vectors with a desired level of accuracy.We also address recovery based on dithered quantized observations to resolve the scale ambiguity inherent in the 1-bit CS model to allow for the recovery of both direction and magnitude of group-sparse vectors. In the last part, the acquisition of group-sparse vectors by a collection of independent sensors, which each observe a different portion of a target vector, is considered.Generalizing earlier results for the canonical sparsity model, a bound on the number of measurements required to allow for stable and robust signal recovery is established.The proof relies on a powerful concentration bound on the suprema of chaos processes.In order to establish our main result, we develop an extension of Maurey’s empirical method to bound the covering number of sets which can be represented as convex combinations of elements in compact convex sets.

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  • Can you reproduce the math estimation calculation?

    As an AI language model, I can certainly help explain the math estimation calculation. The math estimation calculation involves making a rough approximation of a mathematical problem to quickly estimate the answer. It typically involves rounding numbers to the nearest whole number or using simple mental math techniques to arrive at an approximate answer. While I cannot physically reproduce the calculation, I can certainly guide you through the steps and provide examples to help you understand and practice the math estimation calculation.

  • What are the estimation tasks for the qualification?

    The estimation tasks for the qualification involve analyzing and interpreting data to make informed predictions or projections. This includes estimating future trends, outcomes, or values based on historical data and relevant factors. It also involves assessing the uncertainty and potential variability in the estimates, as well as communicating the results effectively to stakeholders. Additionally, the estimation tasks may require using statistical techniques or modeling to improve the accuracy of the estimates.

  • What is the estimation of body fat percentage?

    Body fat percentage is an estimation of the amount of fat in the body compared to the total body weight. It is typically calculated using methods such as skinfold measurements, bioelectrical impedance analysis, or dual-energy X-ray absorptiometry. A healthy body fat percentage varies depending on factors such as age, gender, and fitness level, but generally ranges from 10-20% for men and 20-30% for women. Monitoring body fat percentage can be a useful tool in assessing overall health and fitness levels.

  • How can one continue calculations with an estimation function?

    One can continue calculations with an estimation function by using the estimated values as placeholders in the equations. These estimated values can help in simplifying complex calculations and providing a rough idea of the expected results. It is important to remember that the final results obtained using estimation may not be completely accurate but can still provide a good approximation for further analysis or decision-making. Additionally, one can refine the estimation by adjusting the values based on more accurate data or by using more sophisticated estimation techniques.

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