Natalia Shenkman.

Source: Brazilian Journal of Probability and Statistics, Volume 34, Number 1, 127--135.

Abstract:
While derivations of the characterization of the $d$-variate exchangeable Marshall–Olkin copula via $d$-monotone sequences relying on basic knowledge in probability theory exist in the literature, they contain a myriad of unnecessary relatively complicated computations. We revisit this issue and provide proofs where all undesired artefacts are removed, thereby exposing the simplicity of the characterization. In particular, we give an insightful analytical derivation of the monotonicity conditions based on the monotonicity properties of the survival probabilities.

Emilia Athayde, Assis Azevedo, Michelli Barros, Víctor Leiva.

Source: Brazilian Journal of Probability and Statistics, Volume 33, Number 2, 301--328.

Abstract:
The Birnbaum–Saunders (BS) distribution has been largely studied and applied. A random variable with BS distribution is a transformation of another random variable with standard normal distribution. Generalized BS distributions are obtained when the normally distributed random variable is replaced by another symmetrically distributed random variable. This allows us to obtain a wide class of positively skewed models with lighter and heavier tails than the BS model. Its failure rate admits several shapes, including the unimodal case, with its change-point being able to be used for different purposes. For example, to establish the reduction in a dose, and then in the cost of the medical treatment. We analyze the failure rates of generalized BS distributions obtained by the logistic, normal and Student-t distributions, considering their shape and change-point, estimating them, evaluating their robustness, assessing their performance by simulations, and applying the results to real data from different areas.

Khamis K. Said, Wei Ning, Yubin Tian.

Source: Brazilian Journal of Probability and Statistics, Volume 33, Number 2, 280--300.

Abstract:
In this paper, we study the change point problem for the skew normal distribution model from the view of model selection problem. The detection procedure based on the modified information criterion (MIC) for change problem is proposed. Such a procedure has advantage in detecting the changes in early and late stage of a data comparing to the one based on the traditional Schwarz information criterion which is well known as Bayesian information criterion (BIC) by considering the complexity of the models. Due to the difficulty in deriving the analytic asymptotic distribution of the test statistic based on the MIC procedure, the bootstrap simulation is provided to obtain the critical values at the different significance levels. Simulations are conducted to illustrate the comparisons of performance between MIC, BIC and likelihood ratio test (LRT). Such an approach is applied on two stock market data sets to indicate the detection procedure.

We present SmartExchange, an algorithm-hardware co-design framework to trade higher-cost memory storage/access for lower-cost computation, for energy-efficient inference of deep neural networks (DNNs). We develop a novel algorithm to enforce a specially favorable DNN weight structure, where each layerwise weight matrix can be stored as the product of a small basis matrix and a large sparse coefficient matrix whose non-zero elements are all power-of-2. To our best knowledge, this algorithm is the first formulation that integrates three mainstream model compression ideas: sparsification or pruning, decomposition, and quantization, into one unified framework. The resulting sparse and readily-quantized DNN thus enjoys greatly reduced energy consumption in data movement as well as weight storage. On top of that, we further design a dedicated accelerator to fully utilize the SmartExchange-enforced weights to improve both energy efficiency and latency performance. Extensive experiments show that 1) on the algorithm level, SmartExchange outperforms state-of-the-art compression techniques, including merely sparsification or pruning, decomposition, and quantization, in various ablation studies based on nine DNN models and four datasets; and 2) on the hardware level, the proposed SmartExchange based accelerator can improve the energy efficiency by up to 6.7$ imes$ and the speedup by up to 19.2$ imes$ over four state-of-the-art DNN accelerators, when benchmarked on seven DNN models (including four standard DNNs, two compact DNN models, and one segmentation model) and three datasets.

In a public-private partnership to develop housing, resident services and hope for 102 working families in Haster Orangewood community, Jamboree Housing Corporation and the City of Anaheim announce...

(PRWeb April 27, 2020)

Read the full story at https://www.prweb.com/releases/jamboree_begins_construction_on_capstone_development_to_change_trajectory_of_neighborhood_in_anaheim_ca/prweb17073166.htm

Changliang Zou, Guanghui Wang, Runze Li.

Source: The Annals of Statistics, Volume 48, Number 1, 413--439.

Abstract:
In multiple change-point analysis, one of the major challenges is to estimate the number of change-points. Most existing approaches attempt to minimize a Schwarz information criterion which balances a term quantifying model fit with a penalization term accounting for model complexity that increases with the number of change-points and limits overfitting. However, different penalization terms are required to adapt to different contexts of multiple change-point problems and the optimal penalization magnitude usually varies from the model and error distribution. We propose a data-driven selection criterion that is applicable to most kinds of popular change-point detection methods, including binary segmentation and optimal partitioning algorithms. The key idea is to select the number of change-points that minimizes the squared prediction error, which measures the fit of a specified model for a new sample. We develop a cross-validation estimation scheme based on an order-preserved sample-splitting strategy, and establish its asymptotic selection consistency under some mild conditions. Effectiveness of the proposed selection criterion is demonstrated on a variety of numerical experiments and real-data examples.

Holger Dette, Weichi Wu.

Source: The Annals of Statistics, Volume 47, Number 6, 3578--3608.

Abstract:
This paper considers the problem of testing if a sequence of means $(mu_{t})_{t=1,ldots ,n}$ of a nonstationary time series $(X_{t})_{t=1,ldots ,n}$ is stable in the sense that the difference of the means $mu_{1}$ and $mu_{t}$ between the initial time $t=1$ and any other time is smaller than a given threshold, that is $|mu_{1}-mu_{t}|leq c$ for all $t=1,ldots ,n$. A test for hypotheses of this type is developed using a bias corrected monotone rearranged local linear estimator and asymptotic normality of the corresponding test statistic is established. As the asymptotic variance depends on the location of the roots of the equation $|mu_{1}-mu_{t}|=c$ a new bootstrap procedure is proposed to obtain critical values and its consistency is established. As a consequence we are able to quantitatively describe relevant deviations of a nonstationary sequence from its initial value. The results are illustrated by means of a simulation study and by analyzing data examples.

Victor Veitch, Daniel M. Roy.

Source: The Annals of Statistics, Volume 47, Number 6, 3274--3299.

Abstract:
Sparse exchangeable graphs on $mathbb{R}_{+}$, and the associated graphex framework for sparse graphs, generalize exchangeable graphs on $mathbb{N}$, and the associated graphon framework for dense graphs. We develop the graphex framework as a tool for statistical network analysis by identifying the sampling scheme that is naturally associated with the models of the framework, formalizing two natural notions of consistent estimation of the parameter (the graphex) underlying these models, and identifying general consistent estimators in each case. The sampling scheme is a modification of independent vertex sampling that throws away vertices that are isolated in the sampled subgraph. The estimators are variants of the empirical graphon estimator, which is known to be a consistent estimator for the distribution of dense exchangeable graphs; both can be understood as graph analogues to the empirical distribution in the i.i.d. sequence setting. Our results may be viewed as a generalization of consistent estimation via the empirical graphon from the dense graph regime to also include sparse graphs.

Zhenguo Gao, Pang Du, Ran Jin, John L. Robertson.

Source: The Annals of Applied Statistics, Volume 14, Number 1, 143--159.

Abstract:
Liver procurement experiments with surface-temperature monitoring motivated Gao et al. ( J. Amer. Statist. Assoc. 114 (2019) 773–781) to develop a variance change-point detection method under a smoothly-changing mean trend. However, the spotwise change points yielded from their method do not offer immediate information to surgeons since an organ is often transplanted as a whole or in part. We develop a new practical method that can analyze a defined portion of the organ surface at a time. It also provides a novel addition to the developing field of functional data monitoring. Furthermore, numerical challenge emerges for simultaneously modeling the variance functions of 2D locations and the mean function of location and time. The respective sample sizes in the scales of 10,000 and 1,000,000 for modeling these functions make standard spline estimation too costly to be useful. We introduce a multistage subsampling strategy with steps educated by quickly-computable preliminary statistical measures. Extensive simulations show that the new method can efficiently reduce the computational cost and provide reasonable parameter estimates. Application of the new method to our liver surface temperature monitoring data shows its effectiveness in providing accurate status change information for a selected portion of the organ in the experiment.

Jeng-Min Chiou, Yu-Ting Chen, Tailen Hsing.

Source: The Annals of Applied Statistics, Volume 13, Number 3, 1430--1463.

Abstract:
Motivated by the study of road segmentation partitioned by shifts in traffic conditions along a freeway, we introduce a two-stage procedure, Dynamic Segmentation and Backward Elimination (DSBE), for identifying multiple changes in the mean functions for a sequence of functional data. The Dynamic Segmentation procedure searches for all possible changepoints using the derived global optimality criterion coupled with the local strategy of at-most-one-changepoint by dividing the entire sequence into individual subsequences that are recursively adjusted until convergence. Then, the Backward Elimination procedure verifies these changepoints by iteratively testing the unlikely changes to ensure their significance until no more changepoints can be removed. By combining the local strategy with the global optimal changepoint criterion, the DSBE algorithm is conceptually simple and easy to implement and performs better than the binary segmentation-based approach at detecting small multiple changes. The consistency property of the changepoint estimators and the convergence of the algorithm are proved. We apply DSBE to detect changes in traffic streams through real freeway traffic data. The practical performance of DSBE is also investigated through intensive simulation studies for various scenarios.

Barack Obama said the “rule of law is at risk” following the justice department’s decision to drop charges against former Trump advisor Mike Flynn, as he issued a stark warning about the long-term impact on the American way of life by his successor.

Jong Hee Park, Yunkyu Sohn.

Source: Bayesian Analysis, Volume 15, Number 1, 133--157.

Abstract:
Dynamic modeling of longitudinal networks has been an increasingly important topic in applied research. While longitudinal network data commonly exhibit dramatic changes in its structures, existing methods have largely focused on modeling smooth topological changes over time. In this paper, we develop a hidden Markov network change-point model (HNC) that combines the multilinear tensor regression model (Hoff, 2011) with a hidden Markov model using Bayesian inference. We model changes in network structure as shifts in discrete states yielding particular sets of network generating parameters. Our simulation results demonstrate that the proposed method correctly detects the number, locations, and types of changes in latent node characteristics. We apply the proposed method to international military alliance networks to find structural changes in the coalition structure among nations.

Stefano Peluso, Siddhartha Chib, Antonietta Mira.

Source: Bayesian Analysis, Volume 14, Number 3, 727--751.

Abstract:
We develop a general Bayesian semiparametric change-point model in which separate groups of structural parameters (for example, location and dispersion parameters) can each follow a separate multiple change-point process, driven by time-dependent transition matrices among the latent regimes. The distribution of the observations within regimes is unknown and given by a Dirichlet process mixture prior. The properties of the proposed model are studied theoretically through the analysis of inter-arrival times and of the number of change-points in a given time interval. The prior-posterior analysis by Markov chain Monte Carlo techniques is developed on a forward-backward algorithm for sampling the various regime indicators. Analysis with simulated data under various scenarios and an application to short-term interest rates are used to show the generality and usefulness of the proposed model.

Roderick J. Little.

Source: Statistical Science, Volume 34, Number 4, 580--583.

Eitan Greenshtein, Ya’acov Ritov.

Source: Statistical Science, Volume 34, Number 2, 224--228.

Abstract:
We present some personal reflections on empirical Bayes/ compound decision (EB/CD) theory following Efron (2019). In particular, we consider the role of exchangeability in the EB/CD theory and how it can be achieved when there are covariates. We also discuss the interpretation of EB/CD confidence interval, the theoretical efficiency of the CD procedure, and the impact of sparsity assumptions.

RU Muller
Jul 1, 1987; 7:1951-1968
Articles

Op-ed by Mr Agustín Carstens, General Manager of the BIS, published in The Business Times Singapore, 13 November 2019.

Neural plasticity due to hearing loss results in tonotopic map changes. Several studies have suggested a relation between hearing loss-induced tonotopic reorganization and tinnitus. This large fMRI study on humans was intended to clarify the relations between hearing loss, tinnitus, and tonotopic reorganization. To determine the differential effect of hearing loss and tinnitus, both male and female participants with bilateral high-frequency hearing loss, with and without tinnitus, and a control group were included. In a total of 90 participants, bilateral cortical responses to sound stimulation were measured with loudness-matched pure-tone stimuli (0.25-8 kHz). In the bilateral auditory cortices, the high-frequency sound-evoked activation level was higher in both hearing-impaired participant groups, compared with the control group. This was most prominent in the hearing loss group without tinnitus. Similarly, the tonotopic maps for the hearing loss without tinnitus group were significantly different from the controls, whereas the maps of those with tinnitus were not. These results show that higher response amplitudes and map reorganization are a characteristic of hearing loss, not of tinnitus. Both tonotopic maps and response amplitudes of tinnitus participants appear intermediate to the controls and hearing loss without tinnitus group. This observation suggests a connection between tinnitus and an incomplete form of central compensation to hearing loss, rather than excessive adaptation. One implication of this may be that treatments for tinnitus shift their focus toward enhancing the cortical plasticity, instead of reversing it.

SIGNIFICANCE STATEMENT Tinnitus, a common and potentially devastating condition, is the presence of a "phantom" sound that often accompanies hearing loss. Hearing loss is known to induce plastic changes in cortical and subcortical areas. Although plasticity is a valuable trait that allows the human brain to rewire and recover from injury and sensory deprivation, it can lead to tinnitus as an unwanted side effect. In this large fMRI study, we provide evidence that tinnitus is related to a more conservative form of reorganization than in hearing loss without tinnitus. This result contrasts with the previous notion that tinnitus is related to excessive reorganization. As a consequence, treatments for tinnitus may need to enhance the cortical plasticity, rather than reverse it.

Phototransduction in Drosophila is mediated by phospholipase C (PLC) and Ca²⁺-permeable TRP channels, but the function of endoplasmic reticulum (ER) Ca²⁺ stores in this important model for Ca²⁺ signaling remains obscure. We therefore expressed a low affinity Ca²⁺ indicator (ER-GCaMP6-150) in the ER, and measured its fluorescence both in dissociated ommatidia and in vivo from intact flies of both sexes. Blue excitation light induced a rapid (tau ~0.8 s), PLC-dependent decrease in fluorescence, representing depletion of ER Ca²⁺ stores, followed by a slower decay, typically reaching ~50% of initial dark-adapted levels, with significant depletion occurring under natural levels of illumination. The ER stores refilled in the dark within 100–200 s. Both rapid and slow store depletion were largely unaffected in InsP₃ receptor mutants, but were much reduced in trp mutants. Strikingly, rapid (but not slow) depletion of ER stores was blocked by removing external Na⁺ and in mutants of the Na⁺/Ca²⁺ exchanger, CalX, which we immuno-localized to ER membranes in addition to its established localization in the plasma membrane. Conversely, overexpression of calx greatly enhanced rapid depletion. These results indicate that rapid store depletion is mediated by Na⁺/Ca²⁺ exchange across the ER membrane induced by Na⁺ influx via the light-sensitive channels. Although too slow to be involved in channel activation, this Na⁺/Ca²⁺ exchange-dependent release explains the decades-old observation of a light-induced rise in cytosolic Ca²⁺ in photoreceptors exposed to Ca²⁺-free solutions.

SIGNIFICANCE STATEMENT Phototransduction in Drosophila is mediated by phospholipase C, which activates TRP cation channels by an unknown mechanism. Despite much speculation, it is unknown whether endoplasmic reticulum (ER) Ca²⁺ stores play any role. We therefore engineered flies expressing a genetically encoded Ca²⁺ indicator in the photoreceptor ER. Although NCX Na⁺/Ca²⁺ exchangers are classically believed to operate only at the plasma membrane, we demonstrate a rapid light-induced depletion of ER Ca²⁺ stores mediated by Na⁺/Ca²⁺ exchange across the ER membrane. This NCX-dependent release was too slow to be involved in channel activation, but explains the decades-old observation of a light-induced rise in cytosolic Ca²⁺ in photoreceptors bathed in Ca²⁺-free solutions.

Today leading international experts on climate change, the IPCC, presented their latest report on the impacts of climate change on humanity, and what we can do about it. It’s a lengthy report, so we’ve shrunk it down to Oxfam's five key takeaways on climate change and hunger. 1. Climate change: the impacts on crops are worse than we thought Climate change has [...]

‘‘—the first 1000 days are a critical window in a child’s development, but let’s not forget this child on day 1,001.’’ School nutrition programmes help to address the +1,001 day gap. Today, perceptions of school gardens are changing in response to increasingly urgent needs for greater food security, environmental protection, more secure livelihoods and better nutrition. School gardens have new multiple [...]

On the frontline of climate change, effects are real and measurable. As climate change evolves, food and agriculture need to follow suit. Rising temperatures, changes in rainfall, erratic weather patterns and the prevalence of pests and diseases resulting from climate change threaten agricultural productivity and therefore undermine global food security. Simultaneously, the world’s population is growing steadily and expected to reach [...]

Climate change is what most of us perceive as the top global threat, and the dangers it poses affect present and future generations alike.  How global warming is threatening the planet has been a theme in children’s books for all ages for some time.   How everyone, especially today’s youth, can make a difference to the future of the world [...]

Migration has always existed. It has been a means to reunite with family, to find better jobs, to have a new experience or to start a better life. In 2015, the number of people migrating was up to 1 out of every 7 people in the world.   When it is a choice, migration can be a good way to spread [...]

It is well known that forests, especially rainforests, are key allies in our fight against climate change as they absorb greenhouse gas emissions. But did you know that oceans are the earth’s main buffer against climate change? In fact, about 25 percent of the greenhouse gases that we emit actually gets absorbed by the oceans, as does over 90 percent [...]

Laxmi Sunar wants to provide her daughter with the best possible education so that she can have a bright future. This is Laxmi’s dream; it is the dream that all mothers have for their children. Today though, Laxmi’s main concern is that her family has enough food to eat.

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