[London], [between 1820 and 1829?]

Liverpool (82, Duke Street) ; And in London (13 St. James's Place, Hampstead Road) : Published ... by the artist, April 10th. 1854.

Liverpool (82, Duke Street) ; And in London (13 St. James's Place, Hampstead Road) : Published ... by the artist, April 10th. 1854.

London (in Cheapside) : Published according to Act of Parliament, by J Boydell engraver, 1763.

[Rome?], [between 1600 and 1699]

[Rome?]

Si stampano in Roma (alla Pace ; all'insegna di Parigi) : per Giovan Jacomo Rossi, [1641?]

In Roma [Rome] (alla Pace) : Gio. Iacomo Rossi le stampa ... cum privil. S.P.

[Paris] : Calcographie du Louvre, Musées Imperiaux, [1849?]

[Edinburgh], [between 1788 and 1797]

[between 1700 and 1799]

[between 1700 and 1799]

[between 1700 and 1799]

[between 1700 and 1799]

[between 1700 and 1799]

A Paris (rue St Jacques au dessus de celle des Mathurins au Gd. St. Remy : ches Huquier fils, graveur, [between 1700 and 1799]

Se vend a Augsbourg [Augsburg] : Au Negoce com(m)un de l'Academie Imperiale d'Empire des Arts Liberaux avec Privilege de Sa Majesté Impériale et avec defense ni d'en faire ni de vendre les copie, [between 1700 and 1799]

A Paris (rue St. Jacques au dessus de la fontaine St Severin aux 2 colonne no 257) : chez J. Chereau, [between 1700 and 1799]

[London] (No 69 St Paul's Churchyard) : Printed for Carington Bowles ; [London] (opposite Fetter Lane, Fleet Street) : Robt. Sayer ; [London] (in Cornhil) : Robert Wilkinson, [between 1700 and 1799]

[London] (in St Pauls Churchyard) : Printed for T. Bowles ; [London] (at the Black Horse in Cornhil) : John Bowles & Son ; [London] (opposite Fetter Lane in Fleet Street) : R. Sayer, [between 1700 and 1799]

A Paris : chez Mondhare, [between 1760 and 1792]

A Paris (rue St Jacques au dessus de la fontaine St Severin aux 2 colonnes) : chez Jacques Chereau, [between 1700 and 1799?]

Se vend a Augsbourg [Augsburg] : Au Negoce com(m)un de l'Academie Imperiale d'Empire des Arts libereaux avec privilege de Sa Majesté Impériale et avec defense ni d'en faire ni de vendre les copies, [between 1700 and 1799]

A Paris (rue St Jacques au dessus de celle des Mathurins au Gd. St. Remy) : ches Huquier fils, graveur, [between 1700 and 1799]

[Paris] : [de l'Imprimerie de Clousier], [between 1780 and 1789]

London (Old Bond Street) : published by John Warren ; [London] (Ave Maria Lane) : G & W.B. Whittaker, [between 1800 and 1899]

[London] : [Richard Baldwin], [1752]

[Paris] : [Pillet aîné], [between 1827 and 1839?]

[The Netherlands] : [Romeyn de Hooghe?], [1678?]

[Paris] : [publisher not identified], 1782.

[The Netherlands] : [publisher not identified], [1688]

[London] (Historic Gallery, Pall Mall) : Published by R. Bowyer, June 1804

Back is Martin Luther King Jr.'s "I Have a Dream" speech. Back is Roe v. Wade. Back is climate change. and the word "democratic." A new proposal incorporating those revisions was presented to the Michigan board of education last week.

A federal investigation of Chicago's failures to respond to sexual violence in schools raises troubling questions for school districts nationwide.

How to tune in to Tom Wilson's best games on Sunday.

A 24-team Stanley Cup Playoffs? Here's a look at the latest NHL buzz and a hypothetical Flyers matchup. By Jordan Hall

Troy Brouwer scored the game-winning goal as the Capitals beat the Blackhawks at Nationals Park on Jan. 1, 2015. Relive the excitement with Monday night's replay.

Washington, D.C. : Department of Transportation, Federal Railroad Administration, 1976.

Over four years in Eugene, Ruthy Hebard has made a name for herself with reliability and dynamic play. She's had many memorable moments in a Duck uniform. But her career day against Washington State (34 points), her moment reaching 2,000 career points and her NCAA record for consecutive made FGs (2018) tops the list. Against the Trojans, she set the record (30) and later extended it to 33.

Given a response $Y$ and a vector $X = (X^1, dots, X^d)$ of $d$ predictors, we investigate the problem of inferring direct causes of $Y$ among the vector $X$. Models for $Y$ that use all of its causal covariates as predictors enjoy the property of being invariant across different environments or interventional settings. Given data from such environments, this property has been exploited for causal discovery. Here, we extend this inference principle to situations in which some (discrete-valued) direct causes of $ Y $ are unobserved. Such cases naturally give rise to switching regression models. We provide sufficient conditions for the existence, consistency and asymptotic normality of the MLE in linear switching regression models with Gaussian noise, and construct a test for the equality of such models. These results allow us to prove that the proposed causal discovery method obtains asymptotic false discovery control under mild conditions. We provide an algorithm, make available code, and test our method on simulated data. It is robust against model violations and outperforms state-of-the-art approaches. We further apply our method to a real data set, where we show that it does not only output causal predictors, but also a process-based clustering of data points, which could be of additional interest to practitioners.

We develop an encompassing framework for matching, covariate balancing, and doubly-robust methods for causal inference from observational data called generalized optimal matching (GOM). The framework is given by generalizing a new functional-analytical formulation of optimal matching, giving rise to the class of GOM methods, for which we provide a single unified theory to analyze tractability and consistency. Many commonly used existing methods are included in GOM and, using their GOM interpretation, can be extended to optimally and automatically trade off balance for variance and outperform their standard counterparts. As a subclass, GOM gives rise to kernel optimal matching (KOM), which, as supported by new theoretical and empirical results, is notable for combining many of the positive properties of other methods in one. KOM, which is solved as a linearly-constrained convex-quadratic optimization problem, inherits both the interpretability and model-free consistency of matching but can also achieve the $sqrt{n}$-consistency of well-specified regression and the bias reduction and robustness of doubly robust methods. In settings of limited overlap, KOM enables a very transparent method for interval estimation for partial identification and robust coverage. We demonstrate this in examples with both synthetic and real data.

John J. Dziak, Donna L. Coffman, Matthew Reimherr, Justin Petrovich, Runze Li, Saul Shiffman, Mariya P. Shiyko.

Source: Statistics Surveys, Volume 13, 150--180.

Abstract:
Researchers are sometimes interested in predicting a distal or external outcome (such as smoking cessation at follow-up) from the trajectory of an intensively recorded longitudinal variable (such as urge to smoke). This can be done in a semiparametric way via scalar-on-function regression. However, the resulting fitted coefficient regression function requires special care for correct interpretation, as it represents the joint relationship of time points to the outcome, rather than a marginal or cross-sectional relationship. We provide practical guidelines, based on experience with scientific applications, for helping practitioners interpret their results and illustrate these ideas using data from a smoking cessation study.

Seong-Hwan Jun, Samuel W. K. Wong, James V. Zidek, Alexandre Bouchard-Côté.

Source: The Annals of Applied Statistics, Volume 13, Number 3, 1678--1707.

Abstract:
In this paper, we consider the knot-matching problem arising in computational forestry. The knot-matching problem is an important problem that needs to be solved to advance the state of the art in automatic strength prediction of lumber. We show that this problem can be formulated as a quadripartite matching problem and develop a sequential decision model that admits efficient parameter estimation along with a sequential Monte Carlo sampler on graph matching that can be utilized for rapid sampling of graph matching. We demonstrate the effectiveness of our methods on 30 manually annotated boards and present findings from various simulation studies to provide further evidence supporting the efficacy of our methods.

Ahmed Aziz Ezzat, Mikyoung Jun, Yu Ding.

Source: The Annals of Applied Statistics, Volume 13, Number 3, 1484--1510.

Abstract:
Accurate short-term forecasts are indispensable for the integration of wind energy in power grids. On a wind farm, local wind conditions exhibit sizeable variations at a fine temporal resolution. Existing statistical models may capture the in-sample variations in wind behavior, but are often shortsighted to those occurring in the near future, that is, in the forecast horizon. The calibrated regime-switching method proposed in this paper introduces an action of regime dependent calibration on the predictand (here the wind speed variable), which helps correct the bias resulting from out-of-sample variations in wind behavior. This is achieved by modeling the calibration as a function of two elements: the wind regime at the time of the forecast (and the calibration is therefore regime dependent), and the runlength, which is the time elapsed since the last observed regime change. In addition to regime-switching dynamics, the proposed model also accounts for other features of wind fields: spatio-temporal dependencies, transport effect of wind and nonstationarity. Using one year of turbine-specific wind data, we show that the calibrated regime-switching method can offer a wide margin of improvement over existing forecasting methods in terms of both wind speed and power.

Lekha Patel, Nils Gustafsson, Yu Lin, Raimund Ober, Ricardo Henriques, Edward Cohen.

Source: The Annals of Applied Statistics, Volume 13, Number 3, 1397--1429.

Abstract:
Fluorescing molecules (fluorophores) that stochastically switch between photon-emitting and dark states underpin some of the most celebrated advancements in super-resolution microscopy. While this stochastic behavior has been heavily exploited, full characterization of the underlying models can potentially drive forward further imaging methodologies. Under the assumption that fluorophores move between fluorescing and dark states as continuous time Markov processes, the goal is to use a sequence of images to select a model and estimate the transition rates. We use a hidden Markov model to relate the observed discrete time signal to the hidden continuous time process. With imaging involving several repeat exposures of the fluorophore, we show the observed signal depends on both the current and past states of the hidden process, producing emission probabilities that depend on the transition rate parameters to be estimated. To tackle this unusual coupling of the transition and emission probabilities, we conceive transmission (transition-emission) matrices that capture all dependencies of the model. We provide a scheme of computing these matrices and adapt the forward-backward algorithm to compute a likelihood which is readily optimized to provide rate estimates. When confronted with several model proposals, combining this procedure with the Bayesian Information Criterion provides accurate model selection.