# Lab 1

Lab 1 introduces you to the concept of ML estimates of the true population size given particular parameter values. This lab uses the kalman filter to fit the CDA to the data. You'll explore how the fit changes when you assign the variability to process versus non-process error.

How to run the lab:

At the matlab prompt, type 'Lab1'.

You'll be asked to enter a data code. Type 0 and see the available data. Now, you'll pick an animal.

Next you'll be asked to enter mu, process error, and non-process error. You'll be asked for this 3 times; this will produce 3 plots with your 3 inputed parameter sets.

FYI: Biologically reasonable values of pe and npe are 0.000001 to 0.3 (or so).

Click on one of the exercises below (or in the left nav bar) to start.

Choose a section

How to run the lab:

At the matlab prompt, type 'Lab1'.

You'll be asked to enter a data code. Type 0 and see the available data. Now, you'll pick an animal.

Next you'll be asked to enter mu, process error, and non-process error. You'll be asked for this 3 times; this will produce 3 plots with your 3 inputed parameter sets.

FYI: Biologically reasonable values of pe and npe are 0.000001 to 0.3 (or so).

Click on one of the exercises below (or in the left nav bar) to start.

Choose a section

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