% -----------------------
% EKFs
% -----------------------

@article{fahrmeir94,
  title={Dynamic modelling and penalized likelihood estimation for discrete time survival data},
  author={Fahrmeir, Ludwig},
  journal={Biometrika},
  volume={81},
  number={2},
  pages={317--330},
  year={1994},
  publisher={Biometrika Trust}
}

@article{fahrmeir92,
  title={Posterior mode estimation by extended Kalman filtering for multivariate dynamic generalized linear models},
  author={Fahrmeir, Ludwig},
  journal={Journal of the American Statistical Association},
  volume={87},
  number={418},
  pages={501--509},
  year={1992},
  publisher={Taylor \& Francis Group}
}

@article{fahrmeir96,
  title={Smoothing hazard functions and time-varying effects in discrete duration and competing risks models},
  author={Fahrmeir, Ludwig and Wagenpfeil, Stefan},
  journal={Journal of the American Statistical Association},
  volume={91},
  number={436},
  pages={1584--1594},
  year={1996},
  publisher={Taylor \& Francis Group}
}

% -----------------------
% R and armadillo
% -----------------------

@article{sanderson2016armadillo,
  title={Armadillo: a template-based C++ library for linear algebra},
  author={Sanderson, Conrad and Curtin, Ryan},
  journal={Journal of Open Source Software},
  year={2016},
  publisher={Journal of Open Source Software}
}

@Article{Dirk11,
    title = {{Rcpp}: Seamless {R} and {C++} Integration},
    author = {Dirk Eddelbuettel and Romain Fran\c{c}ois},
    journal = {Journal of Statistical Software},
    year = {2011},
    volume = {40},
    number = {8},
    pages = {1--18},
    url = {http://www.jstatsoft.org/v40/i08/},
  }

@Book{Dirk13,
  title = {Seamless {R} and {C++} Integration with {Rcpp}},
  author = {Dirk Eddelbuettel},
  publisher = {Springer},
  address = {New York},
  year = {2013},
  note = {ISBN 978-1-4614-6867-7},
}

@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2016},
    url = {https://www.R-project.org/},
}

@Article{Dirk14,
    title = {RcppArmadillo: Accelerating R with high-performance C++ linear algebra},
    author = {Dirk Eddelbuettel and Conrad Sanderson},
    journal = {Computational Statistics and Data Analysis},
    year = {2014},
    volume = {71},
    month = {March},
    pages = {1054--1063},
    url = {http://dx.doi.org/10.1016/j.csda.2013.02.005},
}

% -----------------------
% Numerical methods
% -----------------------

@article{miller1992,
  title={Algorithm AS 274: Least squares routines to supplement those of Gentleman},
  author={Miller, Alan J},
  journal={Journal of the Royal Statistical Society. Series C (Applied Statistics)},
  volume={41},
  number={2},
  pages={458--478},
  year={1992},
  publisher={JSTOR}
}

@article{gentleman1972,
  title={Basic procedures for large, sparse, or weighted linear least squares problems},
  author={Gentleman, W Morven},
  year={1972},
  publisher={JSTOR}
}

@article{hammarling08,
  title={Updating the QR factorization and the least squares problem},
  author={Hammarling, Sven and Lucas, Craig},
  year={2008}
}

@article{harvey79,
  title={Maximum likelihood estimation of regression models with autoregressive-moving average disturbances},
  author={Harvey, Andrew C and Phillips, Gary DA},
  journal={Biometrika},
  volume={66},
  number={1},
  pages={49--58},
  year={1979},
  publisher={Biometrika Trust}
}

@article{gill74,
  title={Methods for modifying matrix factorizations},
  author={Gill, Philip E and Golub, Gene H and Murray, Walter and Saunders, Michael A},
  journal={Mathematics of Computation},
  volume={28},
  number={126},
  pages={505--535},
  year={1974}
}

@techreport{seeger04,
  title={Low rank updates for the Cholesky decomposition},
  author={Seeger, Matthias},
  year={2004}
}

@book{golub12,
  title={Matrix computations},
  author={Golub, Gene H and Van Loan, Charles F},
  volume={4},
  year={2012},
  publisher={JHU Press}
}

% -----------------------
% UKFS
% -----------------------

@article{lee10,
  title={Sequential dynamic classification using latent variable models},
  author={Lee, Seung Min and Roberts, Stephen J},
  journal={The Computer Journal},
  volume={53},
  number={9},
  pages={1415--1429},
  year={2010},
  publisher={Br Computer Soc}
}

@article{menegaz16,
  title={Unscented kalman filtering on euclidean and riemannian manifolds},
  author={Menegaz, Henrique Marra Taira},
  year={2016}
}

@inproceedings{julier97,
  title={New extension of the Kalman filter to nonlinear systems},
  author={Julier, Simon J and Uhlmann, Jeffrey K},
  booktitle={AeroSense'97},
  pages={182--193},
  year={1997},
  organization={International Society for Optics and Photonics}
}


@inproceedings{julier02,
  title={The scaled unscented transformation},
  author={Julier, Simon J},
  booktitle={Proceedings of the 2002 American Control Conference (IEEE Cat. No. CH37301)},
  volume={6},
  pages={4555--4559},
  year={2002},
  organization={IEEE}
}

@inproceedings{julier02reduced,
  title={Reduced sigma point filters for the propagation of means and covariances through nonlinear transformations},
  author={Julier, Simon J and Uhlmann, Jeffrey K},
  booktitle={Proceedings of the 2002 American Control Conference (IEEE Cat. No. CH37301)},
  volume={2},
  pages={887--892},
  year={2002},
  organization={IEEE}
}

@inproceedings{julier03,
  title={The spherical simplex unscented transformation},
  author={Julier, Simon J},
  booktitle={American Control Conference, 2003. Proceedings of the 2003},
  volume={3},
  pages={2430--2434},
  year={2003},
  organization={IEEE}
}

@article{julier04,
  title={Unscented filtering and nonlinear estimation},
  author={Julier, Simon J and Uhlmann, Jeffrey K},
  journal={Proceedings of the IEEE},
  volume={92},
  number={3},
  pages={401--422},
  year={2004},
  publisher={IEEE}
}

@inproceedings{wan00,
  title={The unscented Kalman filter for nonlinear estimation},
  author={Wan, Eric A and Van Der Merwe, Rudolph},
  booktitle={Adaptive Systems for Signal Processing, Communications, and Control Symposium 2000. AS-SPCC. The IEEE 2000},
  pages={153--158},
  year={2000},
  organization={Ieee}
}

@inproceedings{wan07,
  title={A novel simplex unscented transform and filter},
  author={Wan-Chun, Li and Ping, Wei and Xian-Ci, Xiao},
  booktitle={Communications and Information Technologies, 2007. ISCIT'07. International Symposium on},
  pages={926--931},
  year={2007},
  organization={IEEE}
}

@inproceedings{menegaz11,
  title={A new smallest sigma set for the Unscented Transform and its applications on SLAM},
  author={Menegaz, Henrique M and Ishihara, Jo{\~a}o Y and Borges, Geovany A},
  booktitle={2011 50th IEEE Conference on Decision and Control and European Control Conference},
  pages={3172--3177},
  year={2011},
  organization={IEEE}
}

@article{gustafsson12,
  title={Some relations between extended and unscented Kalman filters},
  author={Gustafsson, Fredrik and Hendeby, Gustaf},
  journal={IEEE Transactions on Signal Processing},
  volume={60},
  number={2},
  pages={545--555},
  year={2012},
  publisher={IEEE}
}

@phdthesis{lerner02,
  title={Hybrid Bayesian networks for reasoning about complex systems},
  author={Lerner, Uri N},
  year={2002},
  school={Citeseer}
}

@article{charalampidis11,
  title={Development and numerical investigation of new non-linear Kalman filter variants},
  author={Charalampidis, AC and Papavassilopoulos, GP},
  journal={IET control theory \& applications},
  volume={5},
  number={10},
  pages={1155--1166},
  year={2011},
  publisher={IET}
}

@INPROCEEDINGS{Van01,
  author={R. Van der Merwe and E. A. Wan},
  booktitle={2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221)},
  title={The square-root unscented Kalman filter for state and parameter-estimation},
  year={2001},
  volume={6},
  pages={3461-3464 vol.6},
  keywords={Kalman filters;covariance analysis;filtering theory;nonlinear dynamical systems;nonlinear estimation;numerical stability;parameter estimation;state estimation;EKF;SR-UKF;extended Kalman filter;nonlinear dynamic system;nonlinear system identification;numerical stability;parameter estimation;positive semi-definiteness;square-root unscented Kalman filter;state covariances;state estimation;Computational complexity;Equations;Estimation error;Machine learning;Machine learning algorithms;Neural networks;Nonlinear dynamical systems;Nonlinear systems;Parameter estimation;State estimation},
  doi={10.1109/ICASSP.2001.940586},
  ISSN={1520-6149},
  month={}
}

% -----------------------
% Standard KF
% -----------------------

@article{Shumway06,
  title={Time series analysis and its applications: with R examples},
  author={Shumway, Robert H and Stoffer, David S},
  journal={Springer texts in statistics},
  year={2006},
  publisher={New York: Springer}
}

% -----------------------
% Other
% -----------------------

@misc{rossi80,
  title={Money, Work and Crime: Some Experimental Results},
  author={Rossi, Peter H and Berk, Richard A and Lenihan, Kenneth J},
  year={1980},
  publisher={New York: Academic Press}
}

@article{friedman10,
   author = {Jerome Friedman and Trevor Hastie and Rob Tibshirani},
   title = {Regularization Paths for Generalized Linear Models via Coordinate Descent},
   journal = {Journal of Statistical Software},
   volume = {33},
   number = {1},
   year = {2010},
   keywords = {},
   abstract = {We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, two-class logistic regression, and multi- nomial regression problems while the penalties include ℓ1 (the lasso), ℓ2 (ridge regression) and mixtures of the two (the elastic net). The algorithms use cyclical coordinate descent, computed along a regularization path. The methods can handle large problems and can also deal efficiently with sparse features. In comparative timings we find that the new algorithms are considerably faster than competing methods.},
   issn = {1548-7660},
   pages = {1--22},
   doi = {10.18637/jss.v033.i01},
   url = {https://www.jstatsoft.org/index.php/jss/article/view/v033i01}
}

@article{Leary90,
author = {Dianne P. O’Leary},
title = {Robust Regression Computation Using Iteratively Reweighted Least Squares},
journal = {SIAM Journal on Matrix Analysis and Applications},
volume = {11},
number = {3},
pages = {466-480},
year = {1990},
doi = {10.1137/0611032},

URL = {
        http://dx.doi.org/10.1137/0611032

},
eprint = {http://dx.doi.org/10.1137/0611032}
}
