Assistant Professor email: tkenney@mathstat.dal.ca |

MATH 3090: Advanced Calculus - Fall 2006 |
MATH/CSCI 2112: Discrete Structures I - Winter 2007 |

MATH 2051: Problems in Geometry - Fall 2007 |
MATH/CSCI 2113: Discrete Structures II - Winter 2008 |

MATH 1115: Mathematics for Commerce - Winter 2011 |
MATH 1115: Mathematics for Liberal Arts - Winter 2012 |

MATH 3030X/Y: Abstract Algebra - Fall 2012 and Winter 2013 |
MATH/STAT 3360: Probability - Fall 2014, Fall 2013, Fall 2012, Fall 2011 |

MATH/STAT 2600: Theory of interest - Fall 2014, Fall 2013, Fall 2010 |
MATH/STAT 3460: Intermediate Statistical Theory - Winter 2014 |

ACSC/STAT 3703: Actuarial Models I - Winter 2015 |
ACSC/STAT 3720: Life Contingencies I - Winter 2015, Winter 2016, Winter 2017, Winter 2018 |

ACSC/STAT 4703: Actuarial Models II - Fall 2015, Fall 2016, Fall 2017, Fall 2018 |
ACSC/STAT 4720: Life Contingencies II - Fall 2015, Fall 2016, Fall 2017, Fall 2018 |

I am responsible for maintaining and developing the Actuarial Science program at Dalhousie. Here is a website
giving some details of the current program.

I have interests in a wide variety of topics in areas of pure mathematics, data science and actuarial science.

In data science my particular area of interest is the application of statistical techniques to microbiome data. Some particular topics of interest include understanding the temporal dynamics of the microbiome; developing methods for discerning discriminating patterns in the microbiome; and handling the unique measurement error structure in microbiome data. In other areas of data science, I am working on a project on automatic diagnosis of emergency department data. This is a big project involving dealing with many difficulties from a statistical standpoint including: the large quantities of free text data; the amount of missing data, with the potential for the missing pattern to change between training and test data; and the structure of the data and diagnoses. In statistical methodology, I have several projects relating to various areas such as ranking problems and model adequacy testing.

I am beginning to develop a research program in Actuarial Science. Topics of interest include: estimating utility functions to find optimal insurance choices for individuals; and assessing the value of information for calculating insurance costs.

In pure mathematics, my research interests mostly fall between universal algebra, logic an combinatorics. Particular areas of interest include partition and congruence lattices; and Coxeter groups.

W. Chen^{*}, T. Kenney^{*}, J. P. Bielawski and H. Gu. | Testing Adequacy for DNA Substitution Models. | BMC Bioinformatics 20(2019) 349 (16 pages). ^{*}‐co-first authors. |

K. A. Dunn^{*}, T. Kenney^{*}, H. Gu and J. P. Bielawski. | Improved inference of site- specific selection pressures under a generalized parametric model of codon evolution. | BMC Evolutionary Biology 19(2019) 19:22 (19 pages). ^{*}‐co-first authors. |

Y. Cai, H. Gu and T. Kenney | Learning Microbial Community Structures with Supervised and Unsupervised Non-negative Matrix Factorization. | Microbiome 5 (2017), (27 pages) |

T. Kenney | Partial Sup Lattices | Theory and Applications of Categories 30 (2015), 305-331 |

M. Abeysunderra, T. Kenney, C. Field and H. Gu | Combining Distance Matrices on Identical Taxon Sets for Multi-Gene Analysis with Singular Value Decomposition. | PLoS ONE 9 (2014), e94279. doi:10.1371/journal.pone.0094279 (14 pages) |

T. Kenney | Coxeter Groups, Coxeter Monoids and the Bruhat Order. | Journal of Algebraic Combinatorics 39 (2014), 719-731 |

T. Kenney and H. Gu | Hessian Calculation for Phylogenetic Likelihood based on the Pruning Algorithm and its Applications | Statistical Applications in Genetics and Molecular Biology, 11 (2012), issue 4, article 14 |

T. Kenney and R. Paré | Categories as Monoids in Span, Rel and Sup, | Cahiers de e Topologie et Géométrie Différentielle Catégoriques, 52 (2011), 209-240 |

T. Kenney | The Path Relation for Directed Planar Graphs, and its Relation to the Free Diad. | Discrete Mathematics 311 (2011), 441-456 |

T. Kenney | Injective Power Objects and the Axiom of Choice | Journal of Pure and Applied Algebra 215 (2011), 131-144 |

T. Kenney | Graphical algebras - a new approach to congruence lattices | Algebra Universalis 64 (2010), 313-338 |

H. Gu, T. Kenney and M. Zhu | Partial Generalized Additive Models: an Information-Theoretic Approach to Selecting Variables and Dealing with Concurvity. | Journal of computational and graphical statistics 19 (2010), 531-551 |

T. Kenney | The General Theory of Diads | Appl. Cat. Struct. 18 (2010), 523-572 |

T. Kenney and R. J. Wood | Tensor Products of Sup Lattices and generalized sup-arrows. | Theory and Applications of Categories 24 (2010), 266-287 |

T. Kenney | Diads and Their Application to Topoi, | Appl. Cat. Struct. 17 (2009), 567-590 |

T. Kenney | Copower Objects and their applications to Finiteness in Topoi, | Theory and Applications of Categories 16 (2006), 923-956 |

T. Kenney | Generating Families in a Topos, | Theory and Applications of Categories 16 (2006), 896-922 |

L. Liu, T. Kenney, J. Van Limbergen and H. Gu. | SuRF: a New Method for Sparse Variable Selection, with Application in Microbiome Data Analysis. |

T. Kenney, T. Huang and H. Gu. | Poisson PCA: Poisson Measurement Error corrected PCA, with Application to Microbiome Data. |

T. Kenney. | Consistency of Ranking Estimators. |

L. Xu, X. Xu, D. Kong, H. Gu And T. Kenney | Stochastic Generalized Lotka-Volterra Model with An Application to Learning Microbial Community Structures |

S. Ling, T. Kenney, C. Field, H. Gu. | Model Combination for Block Missing Data. |

M. Wang, T. Kenney. | The Influence of Utility Functions on Life Insurance Choices. |

T. Kenney. | Abstract Convexity Spaces and Completely Distributive Lattices. |

Y. Cai, H. Gu, T. Kenney. | Deconvolution density estimation with penalized MLE. |

R. Doig, T. Kenney, H. Gu | Negative Binomial PCA for Overdispersed Count Data |

J. Gao, T. Kenney, H. Gu | Ornstein-Uhlenbeck Process and Optimal Sampling for Analysis of Microbiome Data. |

Lihui Liu | PhD. (Co-supervised with H. Gu) | Variable selection methods with application to microbiome data. |

Yun Cai | PhD. (Co-supervised with H. Gu) | Non-negative matrix factorisation for classification of metagenomic data. |

Shen Ling | PhD. (Co-supervised with H. Gu and C. Field) | Machine Learning Methods for Emergency Room Diagnosis. |

Xinyue Zhang | PhD. (Co-supervised with H. Gu) | Use of Convolutional Neural Networks in Estimating House Prices. |

Wensha Zhang | PhD. (Co-supervised with L. Ho) | Variable selection with dependant data. |

Wanru Jia | MSc. (Co-supervised with H. Gu) | Machine learning from X-ray images. |

Junqiu Gao | MSc. (Co-supervised with H. Gu) | Ornstein-Uhlenbeck Process and Optimal Sampling for Analysis of Microbiome Data. |

Mingzhu Wang | MSc. | The Influence of Utility Functions on Insurance Choices |

Tianshu Huang | MSc. (Co-supervised with H. Gu) | Semi-Parametric Principal Component Analysis for Poisson Count Data with Application to Microbiome Data Analysis. |

Hao He | MSc. (Co-supervised with H. Gu) | Robust Ranking and Selection with Heavy-tailed Priors and its Application to Market Basket Analysis. |

Li Li | MSc. (Co-supervised with H. Gu) | Recombination Detection Based on Likelihood and Clustering for DNA and Amino Acid Sequences. |

Yun Cai | MSc. (Co-supervised with H. Gu) | Non-negative matrix factorisation for classification of metagenomic data. |

Wei Dai | MSc. (Co-supervised with H. Gu) | A new Test to Build Confidence Regions using Balanced Minimum Evolution. |

These guides give advice on what are new topics for a number of graduate students, and are based on common mistakes I have seen when supervising students.

COLD (Codon Optimal Likelihood Discoverer) is a program for estimating phylogenetic parameters using maximum likelihood for codon models.

Simple Plot is a program for adaptively projecting multidimensional data into two dimensions.

Adequate Bootstrap is a program for estimating confidence intervals for parameter values that take into account the uncertainty due to model misspecification.

Here are a number of `R`

packages written by me or my students. These will probably be submitted to CRAN when the relevant papers are published.