Functional Data Analysis: An Introduction and Recent Developments.

Functional data analysis (FDA) is a statistical framework that allows for the analysis of curves, images, or functions on higher dimensional domains. The goals of FDA, such as descriptive analyses, classification, and regression, are generally the same as for statistical analyses of scalar-valued or multivariate data, but FDA brings additional challenges due to the high- and infinite dimensionality of observations and parameters, respectively. This paper provides an introduction to FDA, including a description of the most common statistical analysis techniques, their respective software implementations, and some recent developments in the field.

Regression and alignment for functional data and network topology.

In the brain, functional connections form a network whose topological organization can be described by graph-theoretic network diagnostics. These include characterizations of the community structure, such as modularity and participation coefficient, which have been shown to change over the course of childhood and adolescence. To investigate if such changes in the functional network are associated with changes in cognitive performance during development, network studies often rely on an arbitrary choice of preprocessing parameters, in particular the proportional threshold of network edges.

Regression and Alignment for Functional Data and Network Topology.

In the brain, functional connections form a network whose topological organization can be described by graph-theoretic network diagnostics. These include characterizations of the community structure, such as modularity and participation coefficient, which have been shown to change over the course of childhood and adolescence. To investigate if such changes in the functional network are associated with changes in cognitive performance during development, network studies often rely on an arbitrary choice of pre-processing parameters, in particular the proportional threshold of network edges.

Penalized optimal scaling for ordinal variables with an application to international classification of functioning core sets.

Ordinal data occur frequently in the social sciences. When applying principal component analysis (PCA), however, those data are often treated as numeric, implying linear relationships between the variables at hand; alternatively, non-linear PCA is applied where the obtained quantifications are sometimes hard to interpret. Non-linear PCA for categorical data, also called optimal scoring/scaling, constructs new variables by assigning numerical values to categories such that the proportion of variance in those new variables that is explained by a predefined number of principal components (PCs) is maximized.

Supervised learning for analysing movement patterns in a virtual reality experiment.

The projection into a virtual character and the concomitant illusionary body ownership can lead to transformations of one's entity. Both during and after the exposure, behavioural and attitudinal changes may occur, depending on the characteristics or stereotypes associated with the embodied avatar. In the present study, we investigated the effects on physical activity when young students experience being old.

Statistical inference for ordinal predictors in generalized additive models with application to Bronchopulmonary Dysplasia.

Objective: Discrete but ordered covariates are quite common in applied statistics, and some regularized fitting procedures have been proposed for proper handling of ordinal predictors in statistical models. Motivated by a study from neonatal medicine on Bronchopulmonary Dysplasia (BPD), we show how quadratic penalties on adjacent dummy coefficients of ordinal factors proposed in the literature can be incorporated in the framework of generalized additive models, making tools for statistical inference developed there available for ordinal predictors as well.

Results: The approach presented allows to exploit the scale level of ordinally scaled factors in a sound statistical framework.

Human perception of color differences using computer vision system measurements of raw pork loin.

In the food industry, product color plays an important role in influencing consumer choices. Yet, there remains little research on the human ability to perceive differences in product color; therefore, preference testing is subjective rather than based on quantitative colors. Using a de-centralized computer-aided systematic discrimination testing method, we ascertain consumers' ability to discern between systematically varied colors.

Bacterial Colonization within the First Six Weeks of Life and Pulmonary Outcome in Preterm Infants <1000 g.

Bronchopulmonary dysplasia (BPD) is a multifactorial disease mainly provoked by pre- and postnatal infections, mechanical ventilation, and oxygen toxicity. In severely affected premature infants requiring mechanical ventilation, association of bacterial colonization of the lung and BPD was recently disclosed. To analyze the impact of bacterial colonization of the upper airway and gastrointestinal tract on moderate/severe BPD, we retrospectively analyzed nasopharyngeal and anal swabs taken weekly during the first 6 weeks of life at a single center in = 102 preterm infants <1000 g.

Sustainable use of tainted boar meat: Blending is a strategy for processed products.

While forming mixtures is a widely used approach for other raw materials in food industry, it has not yet been systematically analyzed for boar tainted meat. That is why we simultaneously studied four factors relevant for the production of emulsion-type sausages: percentage boar meat (skatole concentrations up to 0.3 μg/g, androstenone up to 3.

Activation of the NF-κB pathway alters the phenotype of MSCs in the tracheal aspirates of preterm infants with severe BPD.

Mesenchymal stromal cells (MSCs) are released into the airways of preterm infants following lung injury. These cells display a proinflammatory phenotype and are associated with development of severe bronchopulmonary dysplasia (BPD). We aimed to characterize the functional properties of MSCs obtained from tracheal aspirates of 50 preterm infants who required invasive ventilation.

Correction: Noise and accustomation: A pilot study of trained assessors' olfactory performance.

[This corrects the article DOI: 10.1371/journal.pone.

Noise and accustomation: A pilot study of trained assessors' olfactory performance.

While recent studies suggest an influence of noise on olfactory performance, it is unclear as to what extent the influence varies between subjects who are accustomed to noise and those who are not. Two groups of panelists were selected: a University panel usually working under silent conditions and an abattoir panel usually working on the slaughter line with abattoir noise. Odor discrimination, odor identification, and odor detection thresholds were studied.

A note on modeling sparse exponential-family functional response curves.

Non-Gaussian functional data are considered and modeling through functional principal components analysis (FPCA) is discussed. The direct extension of popular FPCA techniques to the generalized case incorrectly uses a marginal mean estimate for a model that has an inherently conditional interpretation, and thus leads to biased estimates of population and subject-level effects. The methods proposed address this shortcoming by using either a two-stage or joint estimation strategy.

Interaction of Skatole and Androstenone in the Olfactory Perception of Boar Taint.

This study analyzed odor-odor interactions of two malodorous volatile substances, androstenone and skatole, that may accumulate in fat and meat of uncastrated male (boar) pigs. Therefore, fat samples were collected from 1000+ entire male pig carcasses for sensory evaluation and quantification of boar taint compounds using gas chromatography-mass spectrometry (GC-MS). Each sample was sniffed by 10 trained assessors, resulting in 11 000+ individual ratings, which were subjected to statistical analysis.

Consumers' perception and acceptance of boiled and fermented sausages from strongly boar tainted meat.

Characteristic off-flavours may occur in uncastrated male pigs depending on the accumulation of androstenone and skatole. Feasible processing of strongly tainted carcasses is challenging but gains in importance due to the European ban on piglet castration in 2018. This paper investigates consumers' acceptability of two sausage types: (a) emulsion-type (BOILED) and (b) smoked raw-fermented (FERM).

Testing differentially expressed genes in dose-response studies and with ordinal phenotypes.

When testing for differentially expressed genes between more than two groups, the groups are often defined by dose levels in dose-response experiments or ordinal phenotypes, such as disease stages. We discuss the potential of a new approach that uses the levels' ordering without making any structural assumptions, such as monotonicity, by testing for zero variance components in a mixed models framework. Since the mixed effects model approach borrows strength across doses/levels, the test proposed can also be applied when the number of dose levels/phenotypes is large and/or the number of subjects per group is small.

Boosting in Nonlinear Regression Models with an Application to DCE-MRI Data.

Background: For the statistical analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data, compartment models are a commonly used tool. By these models, the observed uptake of contrast agent in some tissue over time is linked to physiologic properties like capillary permeability and blood flow. Up to now, models of different complexity have been used, and it is still unclear which model should be used in which situation.

[Value and acceptance of risk assessment for Alzheimer's disease].

Background: It is quite common that people suffering from cognitive impairment only visit a doctor when the symptoms have already reached an advanced stage. This is often due to a fear of Alzheimer’s disease or a dread of exhausting diagnostic procedures and exposure of personal details; however, an early diagnosis and therapy increases the chance of preserving the quality of life for a longer period of time.

Objectives: Evaluation of a risk assessment for Alzheimer’s disease by magnetic resonance imaging (MRI) with respect to the acceptance and value by participants.

Boar taint detection: A comparison of three sensory protocols.

While recent studies state an important role of human sensory methods for daily routine control of so-called boar taint, the evaluation of different heating methods is still incomplete. This study investigated three common heating methods (microwave (MW), hot-water (HW), hot-iron (HI)) for boar fat evaluation. The comparison was carried out on 72 samples with a 10-person sensory panel.

Validation of boar taint detection by sensory quality control: relationship between sample size and uncertainty of performance indicators.

To prevent impaired consumer acceptance due to insensitive sensory quality control, it is of primary importance to periodically validate the performance of the assessors. This communication show cases how the uncertainty of sensitivity and specificity estimates is influenced by the total number of assessed samples and the prevalence of positive (here: boar tainted) samples. Furthermore, a statistically sound approach to determining the sample size that is necessary for performance validation is provided.

Discussion of "the evolution of boosting algorithms" and "extending statistical boosting".

This article is part of a For-Discussion-Section of Methods of Information in Medicine about the papers "The Evolution of Boosting Algorithms - From Machine Learning to Statistical Modelling" and "Extending Statistical Boosting - An Overview of Recent Methodological Developments", written by Andreas Mayr and co-authors. It is introduced by an editorial. This article contains the combined commentaries invited to independently comment on the Mayr et al.

Evaluating the performance of sensory quality control: the case of boar taint.

Detection of malodours referred to as 'boar taint' in entire male pigs is essential for quality control when refraining piglet castration. This study analysed the sensitivity and specificity of sensory evaluation by trained assessors (n=18) compared to chemical analysis of two marker compounds (androstenone, skatole) in backfat (n=794). Taking the measurement uncertainty into consideration, several cut-off thresholds for chemical analysis were exemplarily evaluated.

Rating scales as predictors--the old question of scale level and some answers.

Rating scales as predictors in regression models are typically treated as metrically scaled variables or, alternatively, are coded in dummy variables. The first approach implies a scale level that is not justified, the latter approach results in a large number of parameters to be estimated. Therefore, when rating scales are dummy-coded, applications are often restricted to the use of a few predictors.

How olfactory acuity affects the sensory assessment of boar fat: a proposal for quantification.

Due to animal welfare concerns the production of entire male pigs is one viable alternative to surgical castration. Elevated levels of boar taint may, however, impair consumer acceptance. Due to the lack of technical methods, control of boar taint is currently done using sensory quality control.

Spatially regularized estimation for the analysis of dynamic contrast-enhanced magnetic resonance imaging data.

Competing compartment models of different complexities have been used for the quantitative analysis of dynamic contrast-enhanced magnetic resonance imaging data. We present a spatial elastic net approach that allows to estimate the number of compartments for each voxel such that the model complexity is not fixed a priori. A multi-compartment approach is considered, which is translated into a restricted least square model selection problem.