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Related Concept Videos

Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

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A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
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Types of Global Positioning System Surveys01:30

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GPS surveying methods vary in application, accuracy, and data collection techniques, catering to diverse surveying and mapping needs. Static GPS, kinematic GPS, and real-time kinematic (RTK) surveying are widely used. Each technique offers distinct advantages.Static GPS involves placing one receiver at a known reference point and another at the target point. It collects exact positional data by observing multiple satellite ranges over an extended period, achieving centimeter-level accuracy for...
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Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

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Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...
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Common Leveling Mistakes and Errors01:17

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A survey team is tasked with determining the elevation difference between points Point A and Point B, separated by uneven terrain. They use a leveling instrument and a leveling rod.Common MistakesMisreading the Rod: During a backsight reading at Point A, the instrumentman observes the rod partially obscured by tall grass. Instead of reading 1.135 m, they mistakenly record 1.735 m due to the misalignment of the crosshair with the wrong graduation. This error adds 0.600 m to all subsequent...
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Instrument Calibration01:12

Instrument Calibration

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Instrument calibration is essential for ensuring that instruments produce accurate and consistent results. It is vital in manufacturing, healthcare, testing laboratories, and scientific research. Calibration processes are specific to each instrument and help enhance data accuracy. Each instrument has a unique calibration process tailored to its design and function to improve data accuracy.
Analytical Balance Calibration
An analytical balance measures mass and requires regular calibration to...
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Distance Corrections01:15

Distance Corrections

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To achieve precise distance measurements, especially in surveying and construction, certain corrections must be applied to account for potential sources of error like the standardization errors, temperature variations, and slope adjustments.Standardization error emerges when measurement equipment undergoes changes, such as wear, repairs, or weather impacts. To address this, surveyors compare the equipment’s readings to a standard. This process identifies any deviation that might lead to...
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A global optimisation approach to range-restricted survey calibration.

Ferran Espuny-Pujol1, Karyn Morrissey2, Paul Williamson3

  • 11Health Economics Group, Norwich Medical School, University of East Anglia, Norwich, NR4 7TJ UK.

Statistics and Computing
|January 31, 2020
PubMed
Summary

This study introduces a global optimization (GO) approach for survey calibration, ensuring convergence even with complex data. This method enhances data representativeness and estimate quality by addressing limitations in traditional calibration techniques.

Keywords:
Calibration estimationCalibration weightingDesign-based inferenceGeneralised regressionPenalised calibrationRakingRange restrictionsRidge calibration

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Area of Science:

  • Survey Methodology
  • Statistical Inference
  • Data Science

Background:

  • Survey calibration uses auxiliary information to improve sample representativeness and estimate quality.
  • Traditional calibration methods can fail with sparse data or range restrictions, limiting the use of disaggregated information.
  • Existing solutions for non-convergence offer limited control and may not guarantee a feasible solution.

Purpose of the Study:

  • To present an always-convergent, flexible two-step global optimization (GO) survey calibration approach.
  • To guarantee convergence by allowing controlled adjustments to benchmark constraints or range restrictions.
  • To preserve the desirable properties of calibration estimators while ensuring feasibility.

Main Methods:

  • Developed a two-step global optimization (GO) framework for survey calibration.
  • Incorporated feasibility assessment and automatic, controlled adjustments to benchmark constraints/range restrictions.
  • Formulated and discussed modeling alternatives using various error/change and distance measures.

Main Results:

  • The GO approach guarantees convergence by proactively managing potential infeasibilities.
  • Validated the method by successfully calibrating the 2012 Health Survey for England weights to a highly disaggregated 2011 Census dataset.
  • Demonstrated the preservation of calibration estimator properties under the GO framework.

Conclusions:

  • The proposed global optimization (GO) approach provides a robust and reliable solution for survey calibration.
  • This method enables the effective use of highly disaggregated auxiliary information, overcoming limitations of previous techniques.
  • The GO approach enhances the quality and representativeness of survey estimates in complex scenarios.