Here, we show that mobility indices based on mobile network data significantly improve the performance of the state-of-the-art models in electricity demand forecasting during the sobriety period.
Applications
Ordinal data are quite common in applied statistics.
Methodology Applications
This paper explores how and when to use common random number (CRN) simulation to evaluate MCMC convergence rates.
Computation
However, when sustained use is challenging to satisfy in practice, the usefulness of this estimand can be limited.
Methodology Applications
One can also derive variable importance parameters that measure (and rank) how much of treatment effect heterogeneity is explained by a targeted subset of covariates.
Methodology
With the recent advancements of technology in facilitating real-time monitoring and data collection, "just-in-time" interventions can be delivered via mobile devices to achieve both real-time and long-term management and control.
Methodology
The effect of public health interventions on an epidemic are often estimated by adding the intervention to epidemic models.
Methodology Applications
In this work, the distributional properties of the goodness-of-fit term in likelihood-based information criteria are explored.
Methodology Applications
This article proposes a novel causal discovery and inference method called GrIVET for a Gaussian directed acyclic graph with unmeasured confounders.
Methodology
We discuss multiple classes of piece-wise Pareto-like power law probability density functions $p(x)$ with two regimes, a non-pathological core with non-zero, finite values for support $0\leq x\leq x_{\mathrm{min}}$ and a power-law tail with exponent $-\alpha$ for $x>x_{\mathrm{min}}$.
Methodology Statistics Theory Data Analysis, Statistics and Probability Physics and Society Statistics Theory
