Cristina Rueda

• Ph.D.
• Research Director at University of Valladolid

The Pattern Electroretinogram (PERG) is an essential tool in ophthalmic electrophysiology, providing an objective assessment of the central retinal function. It quantifies the activity of cells in the macula and the ganglion cells of the retina, assisting in the differentiation of macular and optic nerve conditions. In this study, we present the IO...

The identification of unlabeled neuronal electric signals is one of the most challenging open problems in neuroscience, widely known as Spike Sorting. Motivated to solve this problem, we propose a model-based approach within the mixture modeling framework for clustering oscillatory functional data called MixFMM. The core of the approach is the FMM...

The circadian system drives near-24-h oscillations in behaviors and biological processes. The underlying core molecular clock regulates the expression of other genes, and it has been shown that the expression of more than 50 percent of genes in mammals displays 24-h rhythmic patterns, with the specific genes that cycle varying from one tissue to an...

Electroretinogram (ERG) signals measure the electrical activity of the retina in response to different stimulus and play an important role in the diagnosis and monitoring of a broad variety of visual dysfunctions. Specifically, we deal here with the pattern ERG (PERG), an oscillatory signal that registers the response to a structured stimulus of th...

The cardiovascular system is an outstanding example of a circadian pacemaker where heart rate variability (HRV) exhibits rhythmic patterns along 24-h. HRV measures the fluctuations, in milliseconds (ms), of the time intervals between adjacent heartbeats. The 24-h HRV generally exhibits a rhythmic pattern with a pronounced nocturnal acrophase. Thoug...

This paper is focused on the problem of inferring a circular order to solve two different issues arising in the analysis of real data in genomics: the development of a human atlas of circadian gene expressions and a taxonomy of neuronal mouse brain cells. The solutions are derived using different approaches to ordering in a circle the sampling poin...

A bstract The circadian system drives near-24-h oscillations in behaviors and biological processes. The underlying core molecular clock regulates the expression of other genes, and it has been shown that the expression of more than 50 percent of genes in mammals displays 24-h rhythmic patterns, with the specific genes that cycle varying from one ti...

Mathematical models of cardiac electrical activity are one of the most important tools for elucidating information about heart diagnostics. In this paper, we present an efficient mathematical formulation for this modeling simple enough to be easily parametrized and rich enough to provide realistic signals. It relies on a five dipole representation...

This paper is dedicated to the R package FMM which implements a novel approach to describe rhythmic patterns in oscillatory signals. The frequency modulated Möbius (FMM) model is defined as a parametric signal plus a Gaussian noise, where the signal can be described as a single or a sum of waves. The FMM approach is flexible enough to describe a gr...

Background and objective: The automatic diagnosis of heart diseases from the electrocardiogram (ECG) signal is crucial in clinical decision-making. However, the use of computer-based decision rules in clinical practice is still deficient, mainly due to their complexity and a lack of medical interpretation. The objetive of this research is to addre...

The identification of unlabelled neuronal electric signals is one of the most challenging open problems in neuroscience, widely known as Spike Sorting. Motivated to solve this problem, we propose a model-based approach within the mixture modeling framework for clustering oscillatory functional data called MixFMM. The core of the approach is the FMM...

Mathematical models of cardiac electrical activity are one of the most important tools for elucidating information about the heart diagnostic. Even though it is one of the major problems in biomedical research, an efficient mathematical formulation for this modelling has still not been found. In this paper, we present an outstanding mathematical mo...

The automatic diagnosis of heart diseases from the electrocardiogram (ECG) signal is crucial in clinical decision-making. However, the use of computer-based decision rules in clinical practice is still deficient, mainly due to their complexity and a lack of medical interpretation. The objetive of this research is to address these issues by providin...

This paper analyses COVID-19 patients’ dynamics during the first wave in the region of Castilla y León (Spain) with around 2.4 million inhabitants using multi-state competing risk survival models. From the date registered as the start of the clinical process, it is assumed that a patient can progress through three intermediate states until reaching...

The aim of this paper is to present an original approach to estimate the gender pay gap (GPG). We propose a model‐based decomposition, similar to the most popular approaches, where the first component measures differences in group characteristics and the second component measures the unexplained effect; the latter being the real gap. The novel appr...

The complete understanding of the mammalian brain requires exact knowledge of the function of each neuron subpopulation composing its parts. To achieve this goal, an exhaustive, precise, reproducible, and robust neuronal taxonomy should be defined. In this paper, a new circular taxonomy based on transcriptomic features and novel electrophysiologica...

The Hodgkin-Huxley model, decades after its first presentation, is still a reference model in neuroscience as it has successfully reproduced the electrophysiological activity of many organisms. The primary signal in the model represents the membrane potential of a neuron. A simple representation of this signal is presented in this paper. The new pr...

This paper is dedicated to the R package FMM which implements a novel approach to describe rhythmic patterns in oscillatory signals. The frequency modulated M\"obius (FMM) model is defined as a parametric signal plus a gaussian noise, where the signal can be described as a single or a sum of waves. The FMM approach is flexible enough to describe a...

Oscillatory systems arise in the different biological and medical fields. Mathematical and statistical approaches are fundamental to deal with these processes. The Frequency Modulated Mobiüs approach (FMM), reviewed in this paper, is one of these approaches. Little known as it has been recently developed, it solves a variety of exciting questions w...

The complete understanding of the mammalian brain requires exact knowledge of the function of each of the neurons composing its parts. To achieve this goal, an exhaustive, precise, reproducible, and robust neuronal taxonomy should be defined. In this paper, a new circular taxonomy based on transcriptomic features and novel electrophysiological feat...

A novel approach for analysing cardiac rhythm data is presented in this paper. Heartbeats are decomposed into the five fundamental P , Q, R, S and T waves plus an error term to account for artifacts in the data which provides a meaningful, physical interpretation of the heart's electric system. The morphology of each wave is concisely described usi...

Oscillatory systems arise in the different science fields. Complex mathematical formulations with differential equations have been proposed to model the dynamics of these systems. While they have the advantage of having a direct physiological meaning, they are not useful in practice as a result of the parameter adjustment complexity and the presenc...

The aim of this paper is to present an original approach to estimate the gender pay gap. We propose a model-based decomposition, similar to the most popular approaches, where the first component measures differences in group characteristics and the second component measures the unexplained effect; the latter being the real gap. The novel approach i...

In many real classification problems a monotone relation between some predictors and the classes may be assumed when higher (or lower) values of those predictors are related to higher levels of the response. In this paper, we propose new boosting algorithms, based on LogitBoost, that incorporate this isotonicity information, yielding more accurate...

Oscillatory systems arise in the different science fields, very importantly in Neuroscience. Complex mathematical formulations with differential equations have been proposed to model the dynamics of these systems. While they have the advantage of having a direct physiological meaning, they are not useful in practice as a result of the parameter adj...

A novel approach for analysing cardiac rhythm data is presented in this paper. Heartbeats are decomposed into the five fundamental P, Q, R, S and T waves plus an error term to account for artefacts in the data which provides a meaningful, physical interpretation of the heart's electric system. The morphology of each wave is concisely described usin...

This paper introduces a small area estimation approach that borrows strength across domains (areas) and time and is efficiently used to obtain labour force estimators by economic activity. Specifically, the data across time are used to select different models for each domain; such selection is done with an aggregated mixed generalized Akaike inform...

Motivated by applications in physical and biological sciences, we developed a Frequency Modulated Möbius (FMM) model to describe rhythmic patterns in oscillatory systems. Unlike standard symmetric sinusoidal models, FMM is a flexible parametric model that allows deformations to sinusoidal shape to accommodate commonly seen asymmetries in applicatio...

Data derived from microarray technologies are generally subject to various sources of noise and accordingly the raw data are pre-processed before formally analysed. Data normalization is a key pre-processing step when dealing with microarray experiments, such as circadian gene-expressions, since it removes systematic variations across arrays. A wid...

A statistical framework for breast-cancer recurrence uses long-term follow-up data and a knowledge of molecular subcategories to model distinct disease stages and to predict the risk of relapse.

Background: Recent studies have demonstrated that women with early stage ER-positive (ER+) and HER2-negative (HER2-) breast cancer have a persistent risk of recurrence and cancer related death up to 20 years post diagnosis, highlighting the chronic nature of ER+ breast cancer and critical need to identify tumor characteristics that are more predict...

Motivation: Gene-expression data obtained from high throughput technologies are subject to various sources of noise and accordingly the raw data are pre-processed before formally analyzed. Normalization of the data is a key pre-processing step, since it removes systematic variations across arrays. There are numerous normalization methods available...

A mixed generalized Akaike information criterion xGAIC is introduced and validated. It is derived from a quasi-log-likelihood that focuses on the random effect and the variability between the areas, and from a generalized degree-of-freedom measure, as a model complexity penalty, which is calculated by the bootstrap. To study the performance of xGAI...

Motivation Many biological processes, such as cell cycle, circadian clock, menstrual cycles, are governed by oscillatory systems consisting of numerous components that exhibit rhythmic patterns over time. It is not always easy to identify such rhythmic components. For example, it is a challenging problem to identify circadian genes in a given tissu...

The aim of circular order aggregation is to find a circular order on a set of n items using angular values from p heterogeneous data sets. This problem is new in the literature and has been motivated by the biological question of finding the order among the peak expression of a group of cell cycle genes. In this paper, two very different approaches...

Applications of circular regression models appear in many different fields such as evolutionary psychology, motor behavior, biology, and, in particular, in the analysis of gene expressions in oscillatory systems. Specifically, for the gene expression problem, a researcher may be interested in modeling the relationship among the phases of cell-cycle...

In recent years, mass spectrometry techniques have helped proteomics to become a powerful tool for the early diagnosis of cancer, as they help to discover protein profiles specific to each pathological state. One of the questions where proteomics is giving useful practical results is that of classifying patients into one of the possible severity le...

The fruitfly compound eye has been broadly used as a model for neurodegenerative diseases. Classical quantitative techniques to estimate the degeneration level of an eye under certain experimental conditions rely either on time consuming histological techniques to measure retinal thickness, or pseudopupil visualization and manual counting. Alternat...

In this chapter, some problems related to oscillatory data are considered. We describe methodology to solve the problem of estimation of angular parameters under order constraints as well as how to make inferences under circular restrictions in von Mises models. Another interesting problem that is dealt in this chapter is the estimation of a common...

The incorporation of additional information into discriminant rules is receiving in- creasing attention as the rules including this information perform better than the usual rules. In this paper we introduce an R package called dawai, which provides the functions that allow to define the rules that take into account this additional information expr...

Several biologically distinct subgroups may coexist within schizophrenia, which may hamper the necessary replicability to translate research findings into clinical practice. Cortical thickness, curvature and area values and subcortical volumes of 203 subjects (121 schizophrenia patients, out of which 64 were first episodes), 60 healthy controls and...

Oscillatory systems in biology are tightly regulated process where the individual components (e.g. genes) express in an orderly manner by virtue of their functions. The temporal order among the components of an oscillatory system may potentially be disrupted for various reasons (e.g. environmental factors). As a result some components of the system...

In some diseases it is well-known that a unimodal mortality pattern exists. A clear example in developed countries is breast cancer, where mortality increased sharply until the nineties and then decreased. This clear unimodal pattern is not necessarily applicable to all regions within a country. In this paper, we develop statistical tools to check...

Abstract Classification rules that incorporate additional information usually present in discrimination problems are receiving certain attention during the last years as they perform better than the usual rules. Fernández, M. A., C. Rueda and B. Salvador (2006): "Incorporating additional information to normal linear discriminant rules," J. Am. Stat...

In many applications one may be interested in drawing inferences regarding the order of a collection of points on a unit circle. Due to the underlying geometry of the circle standard constrained inference procedures developed for Euclidean space data are not applicable. Recently, statistical inference for parameters under such order constraints on...

The degrees of freedom of semiparametric additive monotone models are derived using results about projections onto sums of order cones. Two important related questions are also studied, namely, the definition of estimators for the parameter of the error term and the formulation of specific Akaike Information Criteria statistics. Several alternative...

In many applications, especially in cancer treatment and diagnosis, investigators are interested in classifying patients into various diagnosis groups on the basis of molecular data such as gene expression or proteomic data. Often, some of the diagnosis groups are known to be related to higher or lower values of some of the predictors. The standard...

In this paper, semiparametric monotone mixed models are introduced, solving, in partic-ular, the problems of estimating and bootstrapping. The models are defined in a small area setting, using the assumption that some of the auxiliary variables have a monotone relationship with the response and with the incorporation of linear terms to model other...

Recent studies suggest the involvement of water in the epidemiology of Cyclospora cayetanensis and some microsporidia. A total of 223 samples from four drinking water treatment plants (DWTPs), seven wastewater treatment plants (WWTPs), and six locations of influence (LI) on four river basins from Madrid, Spain, were analyzed from spring 2008 to win...

The hyoid apparatus is made up of three osteocartilaginous elements that go from the base of the cranium to the hyoid bone; the portions, cranially to caudally, are as follow: stylohyal, ceratohyal, and apohyal. Fusion and ossification of these three components will bring about somewhat long stylohyoid processes, whereas the stylohyal portion is th...

A cell division cycle is a well-coordinated process in eukaryotes with cell cycle genes exhibiting a periodic expression over time. There is considerable interest among cell biologists to determine genes that are periodic in multiple organisms and whether such genes are also evolutionarily conserved in their relative order of time to peak expressio...

We propose and discuss improved classification rules when a subset of the predictors is known to be ordered. We compare the performance of the new rules with other standard rules in a restricted normal setting using simulation experiments and real data exposing their good performance.

Hidden Markov Models (HMMs) have been shown to be a flexible tool for modelling complex biological processes. However, choosing the number of hidden states remains an open question and the inclusion of random effects also deserves more research, as it is a recent addition to the fixed effect HMM in many application fields. We present a Bayesian mix...

This paper proposes a new model-based approach to estimate small areas that extends the Fay–Herriot methodology. The new model is additive, with a random term to characterize the inter-area variability and a nonparametric mean function specification, defined using the information on an auxiliary variable. The most significant advantage of the propo...

We introduce multivariate state space models for estimating and forecasting fertility rates that are dynamic alternatives to logistic representations for fixed time points. Strategies are provided for the Kalman filter and for quasi-Newton algorithm initialization, that assure the convergence of the iterative fitting process. The broad impact of th...

PurposeStatistical Process Control (SPC) was applied to monitor patient set-up in radiotherapy and, when the measured set-up error values indicated a loss of process stability, its root cause was identified and eliminated to prevent set-up errors.

In this article we consider general mixed models to derive small area estimators. The fixed part of the models links the area parameters to the auxiliary variables using a shrinkage region. We show how the selection of the shrinkage region depends on two main factors: the inter-area variation and the correlation coefficient of the auxiliaries with...

Statistical Process Control (SPC) was applied to monitor patient set-up in radiotherapy and, when the measured set-up error values indicated a loss of process stability, its root cause was identified and eliminated to prevent set-up errors. Set up errors were measured for medial-lateral (ml), cranial-caudal (cc) and anterior-posterior (ap) dimensio...

We propose and discuss improved Bayes rules to discriminate between two populations using ordered predictors. To address the problem we propose an alternative formulation using a latent space that allows to introduce the information about the order in the theoretical rules. The rules are first defined when the marginal densities are fully known and...

Motivated by a problem encountered in the analysis of cell cycle gene expression data, this article deals with the estimation of parameters subject to order restrictions on a unit circle. A normal eukaryotic cell cycle has four major phases during cell division, and a cell cycle gene has its peak expression (phase angle) during the phase that may c...

In this paper, we introduce logistic models to analyse fertility curves. The models are formulated as linear models of the log odds of fertility and are defined in terms of parameters that are interpreted as measures of level, location and shape of the fertility schedule. This parameterization is useful for the evaluation, and interpretation of fer...

The efficacy of the anti-inflammatory drug Bobel-24 against experimental infection by Cryptosporidium parvum was evaluated in neonatal lambs. The animals were treated by oral administration of the drug at 50 or 500 mg/kg of body weight. The prophylactic/therapeutic treatment was started 4 h before inoculation of the lambs with oocysts and was conti...

The discrimination problem for two normal populations with the same covariance matrix when additional information on the population is available is considered. A study of the robustness properties against training sample contamination of classification rules that incorporate this additional information is performed. These rules have received recent...

This article presents a study analysing the relationships between a set of psychological variables and the time people spend in getting a job. Age and gender are also considered. An expectations-based model to explain motivated behaviour in finding a job is suggested. The Perceived Control Expectancies in Job Finding Scale (PCEJFS) is used as a cog...

The anticryptosporidial activity of Bobel-24 (2,4,6-triiodophenol) was studied for the first time, resulting in a reduction of the in vitro growth of Cryptosporidium of up to 99.6%. In a SCID mouse model of chronic cryptosporidiosis, significant differences (P < 0.05) in oocyst shedding were observed in animals treated with 125 mg/kg/day. These res...

This article presents a study analysing the relationships between a set of psychological variables and the time people spend in getting a job. Age and gender are also considered. An expectations-based model to explain motivated behaviour in finding a job is suggested. The Perceived Control Expectancies in Job Finding Scale (PCEJFS) is used as a cog...

The most useful and broadly known rule in the classical two-group linear normal discriminant analysis is Anderson's rule. In this article we propose some alternative procedures that prove useful when prior constraints on the mean vectors are known. These rules are based on new estimators of the difference of means. We prove under mild conditions th...

Statistical methods of dimension reduction and classification are used to obtain homogeneous local-area clustering with regard to the most relevant demographic parameters. The dimension reduction is conducted in two stages using Principal Component Analysis and a modified k-mean procedure is proposed to determine the final clusters. This clustering...

The 'fitness for purpose' of a probabilistic model designed to assess dietary exposure to pesticides was validated. The model had to meet two prerequisites. First, it should provide more realistic estimates of intake than conservative methods. Second, it should not underestimate 'true' intakes. True intakes were estimated using a duplicate diet stu...

In the context of a normal model, where the mean is constrained to a polyhedral convex cone, a new methodology has been developed for estimating a linear combination of the mean components. The method is based on an application of adapted parametric bootstrap procedures to reduce the bias of the maximum likelihood estimator. The proposed method is...

The authors consider the estimation of linear functions of a multivariate parameter under orthant restrictions. These restrictions are considered both for location models and for the Poisson distribution. For these models, situations are characterized for which the restricted maximum likelihood estimator dominates the unrestricted one for the estim...

This article is motivated by the problem of estimating contrast in a one-way ANOVA model with restrictions in the parameter vector. We prove that when the restrictions are given by a tree order or a simple order the MLE of some contrast has greater MSE than the unrestricted estimator. A similar behaviour of the MLE is exhibited in a general restric...

We consider a random vector X with unimodal density, diagonal covariance matrix, Ω−1, and location parameter θ subject to order restrictions. For this model the maximum likelihood estimator (MLE) X∗ is the so-called isotonic regression. It is well known that, in certain situations, X∗ is not better than X when coordinate estimation is considered. W...

We consider a linear normal modelY=X[theta]+ewith[theta]verifying a linear restriction and the standard estimators [theta](unrestricted MLE) and[theta]* (restricted MLE). We prove that[theta]* is preferable to [theta]using a new and strong criterion which implies the domination under other usual criteria; in particular it is proven that the standar...

Summary We consider a normal model with known diagonal covariance matrix and a vector of means constrained to belong to a polyhedral cone. The standard estimatorsX (unrestricted MLE) andX * (restricted MLE) are compared for estimation of several components of the parameter simultaneously. We show thatX * is preferred toX under several conditions.

We consider random samples from independent uniform populations U(0, θ i ) where the parameters θ i follow a known partial order. The aim of this paper is to compare the restricted and the unrestricted MLE using the universal domination and the squared error criterions when linear functions of the parameter are estimated. We determine functions for...

We consider the problem of estimating a linear function, c′θ, of the mean of a random vector, X -Nk(θ, D), where D is diagonal and known and θ is subject to p linear restrictions. Let X* be the maximum likelihood estimatoi of θ. We establish that for p=2 and any cϵ RkE( c′X* - c′θ )2≥ E( c′X* - c′θ)2 . We also provide conditions which guarantee tha...

Classified high-resolution satellite images are useful to improve the precision of crop area estimates in an area frame survey through the regression estimator. This is the method used for the Regional Inventories of the MARS Project of the IRSA that is briefly described. Some aspects concerning stability are discussed. Regression results seem to b...

It is well known that anomalies are sometimes observed when using the likelihood ratio test (LRT) for testing restricted hypotheses in a normal model. This paper considers a general framework for these anomalies to occur. We provide a condition, that relates the null and the alternative hypotheses, under which the dominance of the LRT is obtained....

This paper considers a likelihood ratio test for testing hypotheses defined by non-oblique closed convex cones, satisfying the so called iteration projection property, in a set of k normal means. We obtain the critical values of the test using the Chi-Bar-Squared distribution. The obtuse cones are introduced as a particular class of cones which are...

En contrastes de hipótesis oblicuas para medias normales se ha demostrado la dominación del test de razón de verosimilitud (TRV). En este contexto consideramos estadísticos definidos por combinaciones lineales de las medias muestrales obteniendo tests para coeficientes fijos y aleatorios. En ambos casos los tests óptimos no tienen en cuenta toda la...