Search results for "Maximum likelihood"
showing 10 items of 53 documents
Compensation of missing wedge effects with sequential statistical reconstruction in electron tomography.
2014
Electron tomography (ET) of biological samples is used to study the organization and the structure of the whole cell and subcellular complexes in great detail. However, projections cannot be acquired over full tilt angle range with biological samples in electron microscopy. ET image reconstruction can be considered an ill-posed problem because of this missing information. This results in artifacts, seen as the loss of three-dimensional (3D) resolution in the reconstructed images. The goal of this study was to achieve isotropic resolution with a statistical reconstruction method, sequential maximum a posteriori expectation maximization (sMAP-EM), using no prior morphological knowledge about …
Warped Gaussian Processes in Remote Sensing Parameter Estimation and Causal Inference
2018
This letter introduces warped Gaussian process (WGP) regression in remote sensing applications. WGP models output observations as a parametric nonlinear transformation of a GP. The parameters of such a prior model are then learned via standard maximum likelihood. We show the good performance of the proposed model for the estimation of oceanic chlorophyll content from multispectral data, vegetation parameters (chlorophyll, leaf area index, and fractional vegetation cover) from hyperspectral data, and in the detection of the causal direction in a collection of 28 bivariate geoscience and remote sensing causal problems. The model consistently performs better than the standard GP and the more a…
The DMT of Real and Quaternionic Lattice Codes and DMT Classification of Division Algebra Codes
2021
In this paper we consider the diversity-multiplexing gain tradeoff (DMT) of so-called minimum delay asymmetric space-time codes. Such codes are less than full dimensional lattices in their natural ambient space. Apart from the multiple input single output (MISO) channel there exist very few methods to analyze the DMT of such codes. Further, apart from the MISO case, no DMT optimal asymmetric codes are known. We first discuss previous criteria used to analyze the DMT of space-time codes and comment on why these methods fail when applied to asymmetric codes. We then consider two special classes of asymmetric codes where the code-words are restricted to either real or quaternion matrices. We p…
Fast Estimation of Diffusion Tensors under Rician noise by the EM algorithm
2016
Diffusion tensor imaging (DTI) is widely used to characterize, in vivo, the white matter of the central nerve system (CNS). This biological tissue contains much anatomic, structural and orientational information of fibers in human brain. Spectral data from the displacement distribution of water molecules located in the brain tissue are collected by a magnetic resonance scanner and acquired in the Fourier domain. After the Fourier inversion, the noise distribution is Gaussian in both real and imaginary parts and, as a consequence, the recorded magnitude data are corrupted by Rician noise. Statistical estimation of diffusion leads a non-linear regression problem. In this paper, we present a f…
A study on the degree of relationship between two individuals.
2000
The paper studies the likely degree of relationship between two individuals who could possibly be half sibs. The possible common ancestor was dead, which further complicated the problem. The model used was devised by Thompson [in Rao and Chakraborty (eds): Handbook of Statistics, North-Holland, Amsterdam, 1991] and establishes a correspondence between the possible degree of relationship and certain feasible probability distributions on the number of identical by descent genes. Two statistical approaches are considered: the classical one, in which the maximum likelihood estimation for the parameters of Thompson’s model are obtained, and the Bayesian one, in which the test of the hypothesis o…
Testing Ikonos and Landsat 7 ETM+ Potential for Stand-Level Forest Type Mapping by Soft Supervised Approaches
2003
Forest types can be adopted as a suitable reference for classifying survey units within multipurpose forest resources inventories, at the properly considered level. This kind of hierarchical classification approach integrates an ecologically meaningful per-habitat perspective with practical survey, planning and management requirements. Advanced remote sensing technologies can be valuable tools for a cost-effective implementation of such an approach. In the present paper, data from high (Landsat 7 ETM+) and very high (Ikonos) spatial resolution satellite sensors were tested to understand their potential contribution supporting stand-level forest type mapping under Mediterranean conditions. I…
Detection of Signals in MC–CDMA Using a Novel Iterative Block Decision Feedback Equalizer
2022
This paper presents a technique to mitigate multiple access interference (MAI) in multicarrier code division multiple access (MC-CDMA) wireless communications systems. Although under normal circumstances the MC-CDMA system can achieve high spectral efficiency and resistance towards inter symbol interference (ISI) however when exposed to substantial nonlinear distortion the issue of MAI manifests. Such distortion results when the power amplifiers are driven into saturation or when the transmit signal experiences extreme adverse channel conditions. The proposed technique uses a modified iterative block decision feedback equalizer (IB-DFE) that uses a minimal mean square error (MMSE) receiver …
Model averaging estimation of generalized linear models with imputed covariates
2015
a b s t r a c t We address the problem of estimating generalized linear models when some covariate values are missing but imputations are available to fill-in the missing values. This situation generates a bias-precision trade- off in the estimation of the model parameters. Extending the generalized missing-indicator method proposed by Dardanoni et al. (2011) for linear regression, we handle this trade-off as a problem of model uncertainty using Bayesian averaging of classical maximum likelihood estimators (BAML). We also propose a block model averaging strategy that incorporates information on the missing-data patterns and is computationally simple. An empirical application illustrates our…
Population genetic analysis of bi-allelic structural variants from low-coverage sequence data with an expectation-maximization algorithm
2014
Background Population genetics and association studies usually rely on a set of known variable sites that are then genotyped in subsequent samples, because it is easier to genotype than to discover the variation. This is also true for structural variation detected from sequence data. However, the genotypes at known variable sites can only be inferred with uncertainty from low coverage data. Thus, statistical approaches that infer genotype likelihoods, test hypotheses, and estimate population parameters without requiring accurate genotypes are becoming popular. Unfortunately, the current implementations of these methods are intended to analyse only single nucleotide and short indel variation…
Biophysical parameter retrieval with warped Gaussian processes
2015
This paper focuses on biophysical parameter retrieval based on Gaussian Processes (GPs). Very often an arbitrary transformation is applied to the observed variable (e.g. chlorophyll content) to better pose the problem. This standard practice essentially tries to linearize/uniformize the distribution by applying non-linear link functions like the logarithmic, the exponential or the logistic functions. In this paper, we propose to use a GP model that automatically learns the optimal transformation directly from the data. The so-called warped GP regression (WGPR) presented in [1] models output observations as a parametric nonlinear transformation of a GP. The parameters of such prior model are…