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PFG0074

Advanced Sampling

• Sampling from continuous populations (mainly area frames)

• Ways to use auxiliary information to improve a sampling strategy

• Balanced sampling

• Spatially balanced sampling

• Model-assisted estimation

• Estimation of change

• Basic methods for sample coordination

Syllabus and other information


Syllabus

PFG0074 Advanced Sampling, 4.0 Credits

Subjects

Mathematical Statistics

Education cycle

Postgraduate level

Grading scale

Pass / Failed

Prior knowledge

Sampling, 4hp and Statistics, 10 hp or similar.

Objectives

The objective of the course is to introduce more advanced sampling theory, with a focus on methods suitable for environmental inventories and monitoring. Balanced and spatially balanced sampling will be introduced, as well as general model-assisted estimation. These techniques are used to integrate auxiliary information from registers or remote sensing into the sampling strategy to improve the estimation of population parameters. The course is built on lectures, exercises and computer exercises. Exercises and computer exercises are mandatory.

Content

• Sampling from continuous populations (mainly area frames) • Ways to use auxiliary information to improve a sampling strategy • Balanced sampling • Spatially balanced sampling • Model-assisted estimation • Estimation of change • Basic methods for sample coordination

Responsible department

Department of Forest Resource Management