Search results for "Variable"
showing 10 items of 1674 documents
Estimating crop primary productivity with Sentinel-2 and Landsat 8 using machine learning methods trained with radiative transfer simulations
2019
Abstract Satellite remote sensing has been widely used in the last decades for agricultural applications, both for assessing vegetation condition and for subsequent yield prediction. Existing remote sensing-based methods to estimate gross primary productivity (GPP), which is an important variable to indicate crop photosynthetic function and stress, typically rely on empirical or semi-empirical approaches, which tend to over-simplify photosynthetic mechanisms. In this work, we take advantage of all parallel developments in mechanistic photosynthesis modeling and satellite data availability for an advanced monitoring of crop productivity. In particular, we combine process-based modeling with …
Order-distance and other metric-like functions on jointly distributed random variables
2013
We construct a class of real-valued nonnegative binary functions on a set of jointly distributed random variables, which satisfy the triangle inequality and vanish at identical arguments (pseudo-quasi-metrics). These functions are useful in dealing with the problem of selective probabilistic causality encountered in behavioral sciences and in quantum physics. The problem reduces to that of ascertaining the existence of a joint distribution for a set of variables with known distributions of certain subsets of this set. Any violation of the triangle inequality or its consequences by one of our functions when applied to such a set rules out the existence of this joint distribution. We focus on…
Mixture Hidden Markov Models for Sequence Data: The seqHMM Package in R
2019
Sequence analysis is being more and more widely used for the analysis of social sequences and other multivariate categorical time series data. However, it is often complex to describe, visualize, and compare large sequence data, especially when there are multiple parallel sequences per subject. Hidden (latent) Markov models (HMMs) are able to detect underlying latent structures and they can be used in various longitudinal settings: to account for measurement error, to detect unobservable states, or to compress information across several types of observations. Extending to mixture hidden Markov models (MHMMs) allows clustering data into homogeneous subsets, with or without external covariate…
Nowcasting COVID‐19 incidence indicators during the Italian first outbreak
2020
A novel parametric regression model is proposed to fit incidence data typically collected during epidemics. The proposal is motivated by real-time monitoring and short-term forecasting of the main epidemiological indicators within the first outbreak of COVID-19 in Italy. Accurate short-term predictions, including the potential effect of exogenous or external variables are provided. This ensures to accurately predict important characteristics of the epidemic (e.g., peak time and height), allowing for a better allocation of health resources over time. Parameter estimation is carried out in a maximum likelihood framework. All computational details required to reproduce the approach and replica…
The Max-Product Algorithm Viewed as Linear Data-Fusion: A Distributed Detection Scenario
2019
In this paper, we disclose the statistical behavior of the max-product algorithm configured to solve a maximum a posteriori (MAP) estimation problem in a network of distributed agents. Specifically, we first build a distributed hypothesis test conducted by a max-product iteration over a binary-valued pairwise Markov random field and show that the decision variables obtained are linear combinations of the local log-likelihood ratios observed in the network. Then, we use these linear combinations to formulate the system performance in terms of the false-alarm and detection probabilities. Our findings indicate that, in the hypothesis test concerned, the optimal performance of the max-product a…
Synergetic and redundant information flow detected by unnormalized Granger causality: application to resting state fMRI
2015
Objectives: We develop a framework for the analysis of synergy and redundancy in the pattern of information flow between subsystems of a complex network. Methods: The presence of redundancy and/or synergy in multivariate time series data renders difficult to estimate the neat flow of information from each driver variable to a given target. We show that adopting an unnormalized definition of Granger causality one may put in evidence redundant multiplets of variables influencing the target by maximizing the total Granger causality to a given target, over all the possible partitions of the set of driving variables. Consequently we introduce a pairwise index of synergy which is zero when two in…
Ensemble properties of securities traded in the NASDAQ market
2001
We study the price dynamics of stocks traded in the NASDAQ market by considering the statistical properties of an ensemble of stocks traded simultaneously. For each trading day of our database, we study the ensemble return distribution by extracting its first two central moments. According to previous results obtained for the NYSE market, we find that the second moment is a long-range correlated variable. We compare time-averaged and ensemble-averaged price returns and we show that the two averaging procedures lead to different statistical results.
Variable X-ray emission from the accretion shock in the classical T Tauri star V2129 Ophiuchi
2011
The soft X-ray emission from high density plasma in CTTS is associated with the accretion process. It is still unclear whether this high density cool plasma is heated in the accretion shock, or if it is coronal plasma fed/modified by the accretion process. We conducted a coordinated quasi-simultaneous optical and X-ray observing campaign of the CTTS V2129 Oph (Chandra/HETGS data to constrain the X-ray emitting plasma components, and optical observations to constrain the characteristics of accretion and magnetic field). We analyze a 200 ks Chandra/HETGS observation of V2129 Oph, subdivided into two 100 ks segments, corresponding to two different phases within one stellar rotation. The X-ray …
Public transportation and fear of crime at BRT Systems: Approaching to the case of Barranquilla (Colombia) through integrated choice and latent varia…
2021
Abstract Security perception and Fear of Crime (FoC) in urban scenarios have the potential to affect travel behavior, changing people’s travel choices and patterns. In this sense, the feeling of being “safe” or “at-risk” in public transportation not only depends on observable factors like illumination, travel companionship or transport crowding, but also on unobservable individual-specific latent attributes, among which fear of crime constitutes a major issue to consider in transport security policy-making. This study aimed to describe the relationships among sociodemographic features, travel situations, system-design features, and the Fear of Crime at three different locations (buses, bus …
Horseshoe-shaped maps in chaotic dynamics of long Josephson junction driven by biharmonic signals
2000
Abstract A collective coordinate approach is applied to study chaotic responses induced by an applied biharmonic driven signal on the long Josephson junction influenced by a constant dc-driven field with breather initial conditions. We derive a nonlinear equation for the collective variable of the breather and a new version of the Melnikov method is then used to demonstrate the existence of Smale horseshoe-shaped maps in its dynamics. Additionally, numerical simulations show that the theoretical predictions are well reproduced. The subharmonic Melnikov theory is applied to study the resonant breathers. Results obtained using this approach are in good agreement with numerical simulations of …