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Prenatal phthalate exposures and adiposity outcomes trajectories: a multivariate Bayesian factor regression approach
Phuc H. Nguyen, Stephanie M. Engel, Amy H. Herring
https://arxiv.org/abs/2506.02518

Prenatal phthalate exposures and adiposity outcomes trajectories: a multivariate Bayesian factor regression approach
We aim to assess the longitudinal effects of prenatal exposure to phthalates on the risk of childhood obesity in children aged 4 to 7, with potential time-varying and sex-specific effects. Multiple body-composition-related outcomes, such as BMI z-score, fat mass percentage, and waist circumference, are available in the data. Existing chemical mixture analyses often look at these outcomes individually due to the limited availability of multivariate models for mixture exposures. We propose a mult…

Large-Scale Estimation under Unknown Heteroskedasticity
Sheng Chao Ho
https://arxiv.org/abs/2507.02293 https://arxiv.org/pdf/2507.022…

Large-Scale Estimation under Unknown Heteroskedasticity
This paper studies nonparametric empirical Bayes methods in a heterogeneous parameters framework that features unknown means and variances. We provide extended Tweedie's formulae that express the (infeasible) optimal estimators of heterogeneous parameters, such as unit-specific means or quantiles, in terms of the density of certain sufficient statistics. These are used to propose feasible versions with nearly parametric regret bounds of the order of $(\log n)^κ/ n$. The estimators are employed…

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https://mastodon.social/@VeroniqueB99/114604050608739836

Vee (@VeroniqueB99@mastodon.social)
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Failure by Interference: Language Models Make Balanced Parentheses Errors When Faulty Mechanisms Overshadow Sound Ones
Daking Rai, Samuel Miller, Kevin Moran, Ziyu Yao
https://arxiv.org/abs/2507.00322

Failure by Interference: Language Models Make Balanced Parentheses Errors When Faulty Mechanisms Overshadow Sound Ones
Despite remarkable advances in coding capabilities, language models (LMs) still struggle with simple syntactic tasks such as generating balanced parentheses. In this study, we investigate the underlying mechanisms behind the persistence of these errors across LMs of varying sizes (124M-7B) to both understand and mitigate the errors. Our study reveals that LMs rely on a number of components (attention heads and FF neurons) that independently make their own predictions. While some components reli…

An investigation of a varying G through Strong Lensing and SNe Ia observations
R. F. L. Holanda, M. Ferreira, Javier E. Gonzalez
https://arxiv.org/abs/2508.00075 https://…

An investigation of a varying G through Strong Lensing and SNe Ia observations
In this paper, we analyze the potential variation of the gravitational constant $G$ using data from strong gravitational lensing systems and Type Ia supernovae. Testing $G(z)$ parameterizations where $G(z) = G_0(1 + G_1z)$ and $G(z) = G_0(1 + z)^{G_1}$, we also account for the influence of $G$ on the luminosity of SNe Ia through the Chandrasekhar mass-luminosity relation. Only the flat universe hypothesis is considered. Constraints from 158 lensing systems and the Pantheon+ sample show no signi…

Fractional order entropy-based decision-making models under risk
Poulami Paul, Chanchal Kundu
https://arxiv.org/abs/2507.02683 https://

Fractional order entropy-based decision-making models under risk
The construction of an efficient portfolio with a good level of return and minimal risk depends on selecting the optimal combination of stocks. This paper introduces a novel decision-making framework for stock selection based on fractional order entropy due to Ubriaco. By tuning the fractional parameter, the model captures varying attitudes of individuals toward risk. Values of fractional parameter near one indicate high risk tolerance (adventurous attitude), while those near zero reflect risk …

La gira de Sex Pistols con Frank Carter viene a Chile
Martes 9 de septiembre en el Teatro Caupolicšn. La venta de entradas comienza este viernes 4 de julio por puntoticket.
https://hypermusica.cl/los-sex-pistols-con-frank-carter-llegan-al…

Tensor-based reduction of linear parameter-varying state-space models
Bogoljub Terzin, E. Javier Olucha, Amritam Das, Siep Weiland, Roland T\'oth
https://arxiv.org/abs/2507.23591

Tensor-based reduction of linear parameter-varying state-space models
The Linear Parameter-Varying (LPV) framework is a powerful tool for controlling nonlinear and complex systems, but the conversion of nonlinear models into LPV forms often results in high-dimensional and overly conservative LPV models. To be able to apply control strategies, there is often a need for model reduction in order to reduce computational needs. This paper presents the first systematic approach for the joint reduction of state order and scheduling signal dimension of LPV state space mo…

This https://arxiv.org/abs/2112.14249 has been replaced.
link: https://scholar.google.com/scholar?q=a

Nested Nonparametric Instrumental Variable Regression
Several causal parameters in short panel data models are functionals of a nested nonparametric instrumental variable regression (nested NPIV). Recent examples include mediated, time varying, and long term treatment effects identified using proxy variables. In econometrics, examples arise in triangular simultaneous equations and hedonic price systems. However, it appears that explicit mean square convergence rates for nested NPIV are unknown, preventing inference on some of these parameters with…

Forecasting the Impact of Source Galaxy Photometric Redshift Uncertainties on the LSST $3\times2$pt Analysis
Tianqing Zhang, Husni Almoubayyed, Rachel Mandelbaum, Markus Michael Rau, Nikolina \v{S}ar\v{c}evi\'c, C. Danielle Leonard, Jeffrey A. Newman, Brett Andrews, Shuang Liang, The LSST Dark Energy Science Collaboration
https://

Forecasting the Impact of Source Galaxy Photometric Redshift Uncertainties on the LSST $3\times2$pt Analysis
Photometric redshifts of the source galaxies are a key source of systematic uncertainty in the Rubin Observatory Legacy Survey of Space and Time (LSST)'s galaxy clustering and weak lensing analysis, i.e., the $3\times 2$pt analysis. This paper introduces a Fisher forecast code FisherA2Z for the LSST Year 10 (Y10) $3 \times 2$pt and cosmic shear analyses, utilizing a 15-parameter redshift distribution model, with one redshift bias, variance, and outlier rate per tomographic bin. FisherA2Z employ…