ADMB Developer Hiring Guide

Hiring Guide for ADMB Engineers

Ask the right questions to secure the right ADMB talent among an increasingly shrinking pool of talent.

**ADMB** is a free, open-source software programing language designed specifically for statistical analysis and data management in ecology and evolution. It was developed in 2002 by Jari Oksanen and colleagues at the University of Helsinki, and is currently maintained by a team of developers worldwide. ADMB is available for Windows, Mac, and Linux platforms. **Sources:** * [ADMB website](https://admb-project.org/) * [ADMB documentation](https://admb-project.org/documentation/) * [ADMB paper](https://doi.org/10.1093/bioinformatics/btp229)

First 20 minutes

General ADMB knowledge and experience

The next 20 minutes of the interview should attempt to focus more specifically on the development questions used, and the level of depth and skill the engineer possesses.

What is the role of the PROCEDURE_SECTION in an ADMB model?

The PROCEDURE_SECTION is where the model is defined. This includes the likelihood function and any transformations of the parameters or data. This section is where the statistical model is specified.

Describe the difference between global and local parameters in ADMB.

Global parameters are those that are shared across all the data, while local parameters are specific to each data point or group of data points. Global parameters are defined in the PARAMETER_SECTION, while local parameters are defined in the PROCEDURE_SECTION.

How would you handle missing data in ADMB?

In ADMB, missing data can be handled by using the 'naflag' function. This function checks if a value is missing and if so, it treats it as a missing value during the model fitting process.

What are the main components of an ADMB model?

The main components of an ADMB model include the DATA_SECTION, PARAMETER_SECTION, PROCEDURE_SECTION, and REPORT_SECTION. These sections are used to define the data, parameters, model, and outputs respectively.

Can you explain how you would initialize parameters in ADMB?

To initialize parameters in ADMB, you use the INIT_SECTION. In this section, you define the initial estimates for the parameters. The parameters should be initialized to reasonable starting values for the optimization process.

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What youre looking for early-on

Does the candidate have a good understanding of software development methodologies?

This is important as it affects the efficiency and quality of the development process.

Has the candidate shown an ability to learn new technologies quickly?

The field of ADMB development is constantly evolving, so it's important for the candidate to be able to adapt and learn new technologies.

Does the candidate have experience with similar projects?

Past experience can indicate the candidate's ability to handle the tasks in this role.

Is the candidate able to communicate effectively?

Good communication skills are necessary for understanding project requirements and collaborating with the team.

Has the candidate demonstrated problem-solving skills?

This is important as ADMB development often involves complex problem-solving tasks.

Does the candidate possess strong knowledge in ADMB?

This is crucial as the position requires developing and maintaining ADMB applications.

Next 20 minutes

Specific ADMB development questions

The next 20 minutes of the interview should attempt to focus more specifically on the development questions used, and the level of depth and skill the engineer possesses.

What are the limitations of ADMB?

ADMB has a steep learning curve, particularly for those not familiar with C++ syntax. It also lacks some of the user-friendly features of other software, such as a graphical user interface or data visualization tools. Additionally, error messages can be hard to interpret.

How would you implement a mixed effects model in ADMB?

A mixed effects model can be implemented in ADMB by defining both fixed and random effects in the PROCEDURE_SECTION. The fixed effects are modelled as usual, while the random effects are modelled as parameters with a prior distribution, usually a normal distribution with mean 0 and unknown standard deviation.

Describe the difference between the REPORT_SECTION and the TOP_OF_MAIN_SECTION in ADMB.

The REPORT_SECTION is used to define the outputs of the model, while the TOP_OF_MAIN_SECTION is used to perform actions before the model is run. For example, the TOP_OF_MAIN_SECTION might be used to read in data or set initial parameter values.

What are the benefits of using ADMB over other statistical modelling software?

ADMB is particularly well-suited for complex non-linear models and can handle large datasets efficiently. It also allows for a high degree of model customization and has strong support for random effects models.

How would you implement a random walk model in ADMB?

A random walk model can be implemented in ADMB by defining the process model in the PROCEDURE_SECTION. The state at time t is modelled as the state at time t-1 plus some noise. This noise is usually modelled as a normal distribution with mean 0 and unknown standard deviation.

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The ideal back-end app developer

What you’re looking to see on the ADMB engineer at this point.

At this point, a skilled ADMB engineer should display strong analytical thinking, proficiency in ADMB software and coding questions, and problem-solving skills. Red flags would include lack of specific examples of their work or inability to explain complex concepts clearly.

Digging deeper

Code questions

These will help you see the candidate's real-world development capabilities with ADMB.

What does this simple ADMB code do?

DATA_SECTION
  init_int n
  init_vector y(1,n)
PARAMETER_SECTION
  init_bounded_number mu(-10,10)
  init_bounded_number sigma(0,10)
PROCEDURE_SECTION
  nll=-sum(dnorm(y,mu,sigma,1))
REPORT_SECTION
  report << "mu: " << mu << endl;
  report << "sigma: " << sigma << endl;

This code estimates the parameters of a normal distribution. The 'mu' and 'sigma' are the parameters of the normal distribution. The 'dnorm' function calculates the density of the normal distribution. The 'nll' is the negative log-likelihood, which is minimized to find the best fit parameters.

What will be the output of this ADMB code?

DATA_SECTION
  init_int n
  init_vector x(1,n)
PARAMETER_SECTION
  init_bounded_number a(-10,10)
  init_bounded_number b(-10,10)
PROCEDURE_SECTION
  nll=-sum(dnorm(x,a*x+b,1,1))
REPORT_SECTION
  report << "a: " << a << endl;
  report << "b: " << b << endl;

This code will output the estimated parameters 'a' and 'b' of a linear regression model. The 'dnorm' function is used to calculate the density of the normal distribution for the residuals of the model.

What does this ADMB code do related to array manipulation?

DATA_SECTION
  init_int n
  init_vector x(1,n)
  init_vector y(1,n)
PARAMETER_SECTION
  init_bounded_vector a(1,n,-10,10)
PROCEDURE_SECTION
  nll=-sum(dnorm(y,a*x,1,1))
REPORT_SECTION
  for(int i=1;i<=n;i++)
    report << "a[" << i << "]: " << a[i] << endl;

This code estimates the parameters of a multiple linear regression model with 'n' predictors. The 'dnorm' function calculates the density of the normal distribution for the residuals of the model. The 'for' loop in the 'REPORT_SECTION' prints the estimated parameters.

What does this ADMB code do related to threading or concurrency?

DATA_SECTION
  init_int n
  init_vector x(1,n)
  init_vector y(1,n)
PARAMETER_SECTION
  init_bounded_vector a(1,n,-10,10)
PROCEDURE_SECTION
  nll=-sum(dnorm(y,a*x,1,1))
REPORT_SECTION
  #pragma omp parallel for
  for(int i=1;i<=n;i++)
    report << "a[" << i << "]: " << a[i] << endl;

This code estimates the parameters of a multiple linear regression model with 'n' predictors in parallel. The '#pragma omp parallel for' directive tells the compiler to run the 'for' loop in parallel using OpenMP, which can speed up the computation on multi-core processors.

What does this ADMB code do related to class design or class object?

class NormalModel
{
  DATA_SECTION
    init_int n
    init_vector y(1,n)
  PARAMETER_SECTION
    init_bounded_number mu(-10,10)
    init_bounded_number sigma(0,10)
  PROCEDURE_SECTION
    nll=-sum(dnorm(y,mu,sigma,1))
  REPORT_SECTION
    report << "mu: " << mu << endl;
    report << "sigma: " << sigma << endl;
};

This code defines a class 'NormalModel' for estimating the parameters of a normal distribution. The class has data members 'n' and 'y', and parameter members 'mu' and 'sigma'. The 'PROCEDURE_SECTION' calculates the negative log-likelihood, and the 'REPORT_SECTION' prints the estimated parameters.

What does this advanced ADMB code do?

class LogisticModel
{
  DATA_SECTION
    init_int n
    init_vector x(1,n)
    init_vector y(1,n)
  PARAMETER_SECTION
    init_bounded_number a(-10,10)
    init_bounded_number b(-10,10)
  PROCEDURE_SECTION
    nll=-sum(binomial(n,y,a*x+b))
  REPORT_SECTION
    report << "a: " << a << endl;
    report << "b: " << b << endl;
};

This code defines a class 'LogisticModel' for estimating the parameters of a logistic regression model. The class has data members 'n', 'x', and 'y', and parameter members 'a' and 'b'. The 'PROCEDURE_SECTION' calculates the negative log-likelihood using the binomial distribution, and the 'REPORT_SECTION' prints the estimated parameters.

Wrap-up questions

Final candidate for ADMB role questions

The final few interview questions for a ADMB candidate should typically focus on a combination of technical skills, personal goals, growth potential, team dynamics, and company culture.

How would you optimize the performance of ADMB?

Performance in ADMB can be optimized by using efficient coding practices, such as avoiding unnecessary calculations in the PROCEDURE_SECTION, using vectorized operations where possible, and using the sparse matrix capabilities for large datasets. Additionally, the optimization algorithm and settings can be tweaked to improve convergence speed.

How would you validate a model developed in ADMB?

Model validation in ADMB can be done by checking the residuals, using cross-validation, or comparing the model predictions to independent data. Additionally, ADMB provides standard errors for the parameter estimates which can be used to construct confidence intervals.

What are the challenges you might face while implementing a complex model in ADMB and how would you overcome them?

Some challenges might include defining a suitable model, initializing parameters to reasonable values, and ensuring the model converges. These can be overcome by careful model specification, using prior knowledge to initialize parameters, and using diagnostic tools to check model convergence respectively.

Describe the difference between the DATA_SECTION and the PARAMETER_SECTION in ADMB.

The DATA_SECTION is used to define the data that will be used in the model, while the PARAMETER_SECTION is used to define the parameters that will be estimated. The DATA_SECTION is read in before the model is run, while the PARAMETER_SECTION is used during the model fitting process.

How would you handle non-linear models in ADMB?

ADMB is particularly well-suited for non-linear models. These models can be implemented by defining the non-linear relationship in the PROCEDURE_SECTION. ADMB uses a non-linear optimization algorithm to estimate the parameters.

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ADMB application related

Product Perfect's ADMB development capabilities

Beyond hiring for your ADMB engineering team, you may be in the market for additional help. Product Perfect provides seasoned expertise in ADMB projects, and can engage in multiple capacities.

ADMB Consultive assessments

Custom ADMB development projects

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