Paris : V. Adrien Delahaye, 1879.

Paris : Roret, 1834-1854.

Paris : Société d’éditions scientifiques, 1901.

Amstelodami : Typis A. Wolfgang, 1674.

Bruxelles (rue de l'Industrie) : Félix Callewaert père, éditeur, 1875.

[Manchester] : [James Mudd], [between 1800 and 1899]

London : [Published not identified], 1872.

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

Assaf Rabinowicz, Saharon Rosset.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 272--301.

Abstract:
Common model selection criteria, such as $AIC$ and its variants, are based on in-sample prediction error estimators. However, in many applications involving predicting at interpolation and extrapolation points, in-sample error does not represent the relevant prediction error. In this paper new prediction error estimators, $tAI$ and $Loss(w_{t})$ are introduced. These estimators generalize previous error estimators, however are also applicable for assessing prediction error in cases involving interpolation and extrapolation. Based on these prediction error estimators, two model selection criteria with the same spirit as $AIC$ and Mallow’s $C_{p}$ are suggested. The advantages of our suggested methods are demonstrated in a simulation and a real data analysis of studies involving interpolation and extrapolation in linear mixed model and Gaussian process regression.

Norbert Hirschauer, Sven Grüner, Oliver Mußhoff, Claudia Becker, Antje Jantsch.

Source: Statistics Surveys, Volume 14, 71--91.

Abstract:
Besides the inferential errors that abound in the interpretation of $p$-values, the probabilistic pre-conditions (i.e. random sampling or equivalent) for using them at all are not often met by observational studies in the social sciences. This paper systematizes different sampling designs and discusses the restrictive requirements of data collection that are the indispensable prerequisite for using $p$-values.

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.

Michael P. Fay, Michael A. Proschan

Source: Statist. Surv., Volume 4, 1--39.

Abstract:
In a mathematical approach to hypothesis tests, we start with a clearly defined set of hypotheses and choose the test with the best properties for those hypotheses. In practice, we often start with less precise hypotheses. For example, often a researcher wants to know which of two groups generally has the larger responses, and either a t-test or a Wilcoxon-Mann-Whitney (WMW) test could be acceptable. Although both t-tests and WMW tests are usually associated with quite different hypotheses, the decision rule and p-value from either test could be associated with many different sets of assumptions, which we call perspectives. It is useful to have many of the different perspectives to which a decision rule may be applied collected in one place, since each perspective allows a different interpretation of the associated p-value. Here we collect many such perspectives for the two-sample t-test, the WMW test and other related tests. We discuss validity and consistency under each perspective and discuss recommendations between the tests in light of these many different perspectives. Finally, we briefly discuss a decision rule for testing genetic neutrality where knowledge of the many perspectives is vital to the proper interpretation of the decision rule.

Building a scalable machine learning system for unsupervised anomaly detection via representation learning is highly desirable. One of the prevalent methods is using a reconstruction error from variational autoencoder (VAE) via maximizing the evidence lower bound. We revisit VAE from the perspective of information theory to provide some theoretical foundations on using the reconstruction error, and finally arrive at a simpler and more effective model for anomaly detection. In addition, to enhance the effectiveness of detecting anomalies, we incorporate a practical model uncertainty measure into the metric. We show empirically the competitive performance of our approach on benchmark datasets.

Increasing number of sectors which affect human lives, are using Machine Learning (ML) tools. Hence the need for understanding their working mechanism and evaluating their fairness in decision-making, are becoming paramount, ushering in the era of Explainable AI (XAI). In this contribution we introduced a few intrinsically interpretable models which are also capable of dealing with missing values, in addition to extracting knowledge from the dataset and about the problem. These models are also capable of visualisation of the classifier and decision boundaries: they are the angle based variants of Learning Vector Quantization. We have demonstrated the algorithms on a synthetic dataset and a real-world one (heart disease dataset from the UCI repository). The newly developed classifiers helped in investigating the complexities of the UCI dataset as a multiclass problem. The performance of the developed classifiers were comparable to those reported in literature for this dataset, with additional value of interpretability, when the dataset was treated as a binary class problem.

Identification of input data points relevant for the classifier (i.e. serve as the support vector) has recently spurred the interest of researchers for both interpretability as well as dataset debugging. This paper presents an in-depth analysis of the methods which attempt to identify the influence of these data points on the resulting classifier. To quantify the quality of the influence, we curated a set of experiments where we debugged and pruned the dataset based on the influence information obtained from different methods. To do so, we provided the classifier with mislabeled examples that hampered the overall performance. Since the classifier is a combination of both the data and the model, therefore, it is essential to also analyze these influences for the interpretability of deep learning models. Analysis of the results shows that some interpretability methods can detect mislabels better than using a random approach, however, contrary to the claim of these methods, the sample selection based on the training loss showed a superior performance.

In the variational relevance vector machine, the gamma distribution is representative as a hyperprior over the noise precision of automatic relevance determination prior. Instead of the gamma hyperprior, we propose to use the inverse gamma hyperprior with a shape parameter close to zero and a scale parameter not necessary close to zero. This hyperprior is associated with the concept of a weakly informative prior. The effect of this hyperprior is investigated through regression to non-homogeneous data. Because it is difficult to capture the structure of such data with a single kernel function, we apply the multiple kernel method, in which multiple kernel functions with different widths are arranged for input data. We confirm that the degrees of freedom in a model is controlled by adjusting the scale parameter and keeping the shape parameter close to zero. A candidate for selecting the scale parameter is the predictive information criterion. However the estimated model using this criterion seems to cause over-fitting. This is because the multiple kernel method makes the model a situation where the dimension of the model is larger than the data size. To select an appropriate scale parameter even in such a situation, we also propose an extended prediction information criterion. It is confirmed that a multiple kernel relevance vector regression model with good predictive accuracy can be obtained by selecting the scale parameter minimizing extended prediction information criterion.

Machine learning models with both good predictability and high interpretability are crucial for decision support systems. Linear regression is one of the most interpretable prediction models. However, the linearity in a simple linear regression worsens its predictability. In this work, we introduce a locally adaptive interpretable regression (LoAIR). In LoAIR, a metamodel parameterized by neural networks predicts percentile of a Gaussian distribution for the regression coefficients for a rapid adaptation. Our experimental results on public benchmark datasets show that our model not only achieves comparable or better predictive performance than the other state-of-the-art baselines but also discovers some interesting relationships between input and target variables such as a parabolic relationship between CO2 emissions and Gross National Product (GNP). Therefore, LoAIR is a step towards bridging the gap between econometrics, statistics, and machine learning by improving the predictive ability of linear regression without depreciating its interpretability.

Ridge regression (RR) is a regularization technique that penalizes the L2-norm of the coefficients in linear regression. One of the challenges of using RR is the need to set a hyperparameter ($alpha$) that controls the amount of regularization. Cross-validation is typically used to select the best $alpha$ from a set of candidates. However, efficient and appropriate selection of $alpha$ can be challenging, particularly where large amounts of data are analyzed. Because the selected $alpha$ depends on the scale of the data and predictors, it is not straightforwardly interpretable. Here, we propose to reparameterize RR in terms of the ratio $gamma$ between the L2-norms of the regularized and unregularized coefficients. This approach, called fractional RR (FRR), has several benefits: the solutions obtained for different $gamma$ are guaranteed to vary, guarding against wasted calculations, and automatically span the relevant range of regularization, avoiding the need for arduous manual exploration. We provide an algorithm to solve FRR, as well as open-source software implementations in Python and MATLAB (https://github.com/nrdg/fracridge). We show that the proposed method is fast and scalable for large-scale data problems, and delivers results that are straightforward to interpret and compare across models and datasets.

Martin Kolb, Mladen Savov.

Source: Bernoulli, Volume 26, Number 2, 1453--1472.

Abstract:
We derive a criterium for the almost sure finiteness of perpetual integrals of Lévy processes for a class of real functions including all continuous functions and for general one-dimensional Lévy processes that drifts to plus infinity. This generalizes previous work of Döring and Kyprianou, who considered Lévy processes having a local time, leaving the general case as an open problem. It turns out, that the criterium in the general situation simplifies significantly in the situation, where the process has a local time, but we also demonstrate that in general our criterium can not be reduced. This answers an open problem posed in ( J. Theoret. Probab. 29 (2016) 1192–1198).

Denis Talay, Milica Tomašević.

Source: Bernoulli, Volume 26, Number 2, 1323--1353.

Abstract:
In this paper, we analyze a stochastic interpretation of the one-dimensional parabolic–parabolic Keller–Segel system without cut-off. It involves an original type of McKean–Vlasov interaction kernel. At the particle level, each particle interacts with all the past of each other particle by means of a time integrated functional involving a singular kernel. At the mean-field level studied here, the McKean–Vlasov limit process interacts with all the past time marginals of its probability distribution in a similarly singular way. We prove that the parabolic–parabolic Keller–Segel system in the whole Euclidean space and the corresponding McKean–Vlasov stochastic differential equation are well-posed for any values of the parameters of the model.

M Steriade
Aug 1, 1993; 13:3252-3265
Articles

The enterprise IT environment is complex. Many systems, technologies and practices developed at various times coexist in the same world. With expectations for technological advancements at their peak, we're tasked with enabling these systems to work together harmoniously to support the continuous sharing of information. Systems and data must connect as if all information were native to each.

Pattern separation and completion are fundamental hippocampal computations supporting memory encoding and retrieval. However, despite extensive exploration of these processes, it remains unclear whether and how top-down processes adaptively modulate the dynamics between these computations. Here we examine the role of expectation in shifting the hippocampus to perform pattern separation. In a behavioral task, 29 participants (7 males) learned a cue-object category contingency. Then, at encoding, one-third of the cues preceding the to-be-memorized objects, violated the studied rule. At test, participants performed a recognition task with old objects (targets) and a set of parametrically manipulated (very similar to dissimilar) foils for each object. Accuracy was found to be better for foils of high similarity to targets that were contextually unexpected at encoding compared with expected ones. Critically, there were no expectation-driven differences for targets and low similarity foils. To further explore these effects, we implemented a computational model of the hippocampus, performing the same task as the human participants. We used representational similarity analysis to examine how top-down expectation interacts with bottom-up perceptual input, in each layer. All subfields showed more dissimilar representations for unexpected items, with dentate gyrus (DG) and CA3 being more sensitive to expectation violation than CA1. Again, representational differences between expected and unexpected inputs were prominent for moderate to high levels of input similarity. This effect diminished when inputs from DG and CA3 into CA1 were lesioned. Overall, these novel findings strongly suggest that pattern separation in DG/CA3 underlies the effect that violation of expectation exerts on memory.

SIGNIFICANCE STATEMENT What makes some events more memorable than others is a key question in cognitive neuroscience. Violation of expectation often leads to better memory performance, but the neural mechanism underlying this benefit remains elusive. In a behavioral study, we found that memory accuracy is enhanced selectively for unexpected highly similar foils, suggesting expectation violation does not enhance memory indiscriminately, but specifically aids the disambiguation of overlapping inputs. This is further supported by our subsequent investigation using a hippocampal computational model, revealing increased representational dissimilarity for unexpected highly similar foils in DG and CA3. These convergent results provide the first evidence that pattern separation plays an explicit role in supporting memory for unexpected information.

Thieves pilfered "The Parsonage Garden at Nuenen in Spring 1884" from the Singer Laren in the early hours of Monday morning

The City of Timmins says a COVID-19 outbreak remains in place at a long-term care home in the city, even after the one affected resident has now tested negative — twice.

Carmen Figueroa Sotelo has been interpreting all the news conferences for English audiences since the beginning of the pandemic in Quebec

A Saskatchewan woman's helping hand — or window scraper — has gone viral this week, with a video showing her assist a beleaguered porcupine garnering more than 1.2 million views on Facebook.

After several days in which fewer than 400 cases of COVID-19 were added to the provincial tally, Friday's report was up again, with 477 new cases reported.

Long-term workers tell local friends the meaning of ancient traditions, sharing the Bible stories behind their rituals.

There are limited data regarding the current status of the pediatric clinical trial enterprise.

Evaluation of the ClinicalTrials.gov data set allows description of the overall portfolio of clinical trials relevant to US children, which was previously not possible. (Read the full article)

The false-positive rate of newborn screening for classic congenital adrenal hyperplasia (CAH) remains high and has not been significantly improved by adjusting 17α-hydroxyprogesterone cutoff values for birth weight and/or gestational age. In response, 4 states have initiated second-tier steroid profile screening.

Under second-tier screening, the false-positive rate remains high, and classic CAH cases missed by screening (false-negatives) occur more frequently than reported. Physicians are cautioned that a negative screen does not necessarily rule out CAH. (Read the full article)

Herpes encephalitis outside the neonatal period is typically severe and recognizable to clinicians. Excessive testing for herpes encephalitis is associated with increased medical costs and hospital length of stay, and risks patient harm.

Herpes testing and empirical acyclovir treatment in older and less unwell patients has been increasing in US pediatric hospitals over the past decade, which may reflect a more fundamental problem in current approaches to clinical decision-making. (Read the full article)

Family meals are protective for child health, but there are inconsistent findings in relation to child weight status. More research is needed examining why family meals are protective for child health and whether there are differences by child weight status.

The current mixed-methods study used direct observational methods to examine family dynamics during family meals and child weight status. Results indicated that positive family interpersonal and food-related dynamics during family meals were associated with reduced prevalence of childhood obesity. (Read the full article)

This is the first population-based study regarding the epidemiologic characteristics of pediatric zoster among only those who had contracted varicella.

The herpes zoster (HZ) incidence among only children with varicella infection is higher than previously reported. The HZ incidence increased for children contracting varicella aged <2 years. After a vaccination program, the HZ risk increased for those contracting varicella aged ≥2 years. (Read the full article)

Both short and long interpregnancy intervals are associated with increased risk of autism in second-born children. However, it is not known if the association is explained by unfavorable birth outcomes of the previous siblings.

Both short and long interpregnancy intervals increase risk of autism in second-born children independently of previous siblings being born premature, having low birth weight, or being born by cesarean delivery and independently of maternal antidepressant use 3 months before pregnancy. (Read the full article)

As I attended the annual Storage Visions conference a couple of weeks ago, I was struck again by just how much flash is being used in enterprise systems, and what the potential is for future uses going forward.

Ibrexafungerp (formerly SCY-078) is a semisynthetic triterpenoid and potent (1->3)-β-D-glucan synthase inhibitor. We investigated the in vitro activity, pharmacokinetics, and in vivo efficacy of ibrexafungerp (SCY) alone and in combination with anti-mould triazole isavuconazole (ISA) against invasive pulmonary aspergillosis (IPA). The combination of ibrexafungerp and isavuconazole in in vitro studies resulted in an additive and synergistic interactions against Aspergillus spp. Plasma concentration-time curves of ibrexafungerp were compatible with linear dose proportional profile. In vivo efficacy was studied in a well established persistently neutropenic NZW rabbit model of experimental IPA. Treatment groups included untreated rabbits (UC) and rabbits receiving ibrexafungerp at 2.5(SCY2.5) and 7.5(SCY7.5) mg/kg/day, isavuconazole at 40(ISA40) mg/kg/day, or combinations of SCY2.5+ISA40 and SCY7.5+ISA40. The combination of SCY+ISA produced in vitro synergistic interaction. There was significant in vivo reduction of residual fungal burden, lung weights, and pulmonary infarct scores in SCY2.5+ISA40, SCY7.5+ISA40, and ISA40-treatment groups vs that of SCY2.5-treated, SCY7.5-treated and UC (p<0.01). Rabbits treated with SCY2.5+ISA40 and SCY7.5+ISA40 had prolonged survival in comparison to that of SCY2.5-, SCY7.5-, ISA40-treated or UC (p<0.05). Serum GMI and (1->3)-β-D-glucan levels significantly declined in animals treated with the combination of SCY7.5+ISA40 in comparison to those treated with SCY7.5 or ISA40 (p<0.05). Ibrexafungerp and isavuconazole combination demonstrated prolonged survival, decreased pulmonary injury, reduced residual fungal burden, lower GMI and (1->3)-β-D-glucan levels in comparison to those of single therapy for treatment of IPA. These findings provide an experimental foundation for clinical evaluation of the combination of ibrexafungerp and an anti-mould triazole for treatment of IPA.

An early Saúl Ñíguez goal in Madrid means holders Liverpool once again face a second-leg deficit against Spanish visitors.

CyberPower's Gamer Xtreme midtower packs fluid 1080p gaming performance into a quality package, although it's not quite the top value in its class.

Fingerprinters collect information about the device you're accessing the internet on and attempt to build up a profile of the device.

Istanbul is the venue for the first all-English UEFA Super Cup as European champions Liverpool take on Chelsea.

The Glass Enterprise Edition 2.0 boasts a newer Qualcomm processor that promises better performance and battery life. Google also swapped a micro-USB connectiong for a USB-C port that supports faster charging.

The Apple Watch Series 3 GPS plus cellular smartwatch is down to just $229, Walmart's Overpowered gaming desktop is only $699, and the LG G8 ThinQ smartphone is just $500.

An Indian-origin psychiatrist in the US has to pay USD 1,45,000 as settlement to resolve allegations that he overprescribed opioids to his patients outside the usual course of his professional...