mFPCA
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This document introduces multivariate functional principal component analysis (mFPCA). mFPCA is a technique that estimates individual trajectories from sparse longitudinal data for multiple processes simultaneously. It models the response of each individual at each time point as the sum of the mean trajectory, individual deviations due to principal modes of variation, and error. mFPCA determines the principal modes of variation in trajectories across individuals and evaluates the association between these modes of variation among different processes. The document provides the mathematical model for mFPCA, representing the response as a function of basis coefficients for the mean and individual deviations, and illustrates its application to modeling trajectories of multiple brain regions.
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Address correspondence to Nuno
Ricardo Pais Costa, Polytechnic
Institute of Setúbal, Setúbal College
of Technology, Campus do IPS,
Estefanilha, 2910-761 Setúbal,
Portugal. E-mail:
[email protected]
Quality Engineering, 22:140–149, 2010
Copyright # Taylor & Francis Group, LLC
ISSN: 0898-2112 print=1532-4222 online
DOI: 10.1080/08982110903394205
140
(2008). Technical details on RPD can be found in the
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Nuno Ricardo Pais Costa
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Setúbal College of Technology,
Campus do IPS, Setúbal,
Portugal
ABSTRACT Checking whether process and product are satisfying or
functioning according to the technical specification is not enough to assure
competitiveness. Competition compels organizations to develop efforts to
assure that product and process characteristics are on target values and
the variability around those targets is minimal. This article proposes an alter-
native method for optimizing both the mean and standard deviation of a
quality characteristic of the process or product. The objective function
accommodates all the response types, allowing the practitioner to assign dis-
tinct weights to process mean and standard deviation and to find trade-off
solutions between them, taking their relative magnitudes into account.
Two classical examples from the literature are used to illustrate the feasi-
bility of the proposed method and compare its results with those of other
popular methods. A practical procedure for implementing the proposed
method is also presented.
KEYWORDS dual response, GRG, optimization, response surface, robust
design
INTRODUCTION
In the current market, rather than checking whether process and product
are satisfying or functioning according to technical specifications, it is essen-
tial to assure that their characteristics are on target value and the variability
around those targets is minimal. With this aim, various approaches have
been put forward and dissected in the literature.
Response surface methodology (RSM) since the 1950s and robust
parameter design (RPD) since the mid-1980s have been successfully used
in different application areas with various purposes, namely, to get low
variability, low cost, high quality, and high reliability in the process and pro-
duct. RPD has generated a great deal of interest among researchers and
practitioners, although the statistical techniques used have been the subject
of much discussion and controversy. A comprehensive overview at a con-
ceptual level of the importance and usefulness of the principles underlying
RPD, a methodology for implementing them, and proposals of alternative
methods for data analysis is provided by Nair (1992). Recent references
are Robinson et al. (2004), Park et al. (2006), and Arvidsson and Gremyr
Address correspondence to Nuno
Ricardo Pais Costa, Polytechnic
Institute of Setúbal, Setúbal College
of Technology, Campus do IPS,
Estefanilha, 2910-761 Setúbal,
Portugal. E-mail:
[email protected]
Quality Engineering, 22:140–149, 2010
Copyright # Taylor & Francis Group, LLC
ISSN: 0898-2112 print=1532-4222 online
DOI: 10.1080/08982110903394205
140
(2008). Technical details on RPD can be found in the
extensive bibliographies of these references.
The integration of RPD principles with well-
established statistical techniques has been.
1PPA 670 Public Policy AnalysisBasic Policy Terms an.docx
This document provides an overview of key concepts in public policy analysis. It defines public policy as purposive actions by government institutions to address problems and create change. The eight-fold path and process model are introduced as approaches to policy analysis. Key institutions and individuals in the policy environment are discussed. Problem recognition is described as the essential first step, including defining the problem type, scale, location, intensity, extensiveness, and timeline. Cost-benefit analysis is introduced as a tool to evaluate policy alternatives.
A Study On Hybrid System
The document discusses Tom Brimeyer's Hypothyroidism Revolution program, which is a comprehensive guide for reversing hypothyroidism naturally and permanently in three phases. The first phase focuses on eliminating food sensitivities and toxins. The second phase introduces a thyroid-supporting diet. The third phase incorporates a healthy lifestyle including special exercises. The program contains over 160 pages explaining the three phases in detail. It aims to help sufferers of hypothyroidism achieve optimal health through natural means.
Ensemble Filters to Reduce Uncertanties in San Quintin Bay Hidrodynamic System
Ensemble Filters to Reduce Uncertanties in San Quintin Bay Hidrodynamic SystemMariangel (Angie) Garcia, Ph.D
A Delft3D model was implemented for the study of the hydrodynamics of San Quintin Bay. Calibration and validation have been successfully executed in previous research, but uncertainties propagated through simulation of future conditions are mostly unknown, and have not been tested in this region. Data Assimilation (DA) techniques play an important role, as their mathematical methods depict algorithms for combining dynamical system observations, implement computational models describing their evolution, and any relevant prior information. The aim of this study was to make a comparative analysis of calibration methods versus DA, as well as evaluate the long-term predictive capability of a model using sea surface height and current measurements taken within the bay. Delft3D-OpenDA is considered an effective a tool for delivering real-time forecasting via employment of the ensemble Kalman filter algorithm, and this automatic procedure is expected to obtain an improved model forecast. We anticipate an ensemble size of between 40 and 60 will provide the optimal and most accurately predicted water levels for San Quintin Bay by assimilating a single observation point located at the bay’s entry. New computational challenges will also be addressed, as well as means of reducing the computational costs of these implementations.Application of Exponential Gamma Distribution in Modeling Queuing Data
There are many events in daily life where a queue is formed. Queuing theory is the study of waiting lines and it is very crucial in analyzing the procedure of queuing in daily life of human being. Queuing theory applies not only in day to day life but also in sequence of computer programming, networks, medical field, banking sectors etc. Researchers have applied many statistical distributions in analyzing a queuing data. In this study, we apply a new distribution named Exponential Gamma distribution in fitting a data on waiting time of bank customers before service is been rendered. We compared the adequacy and performance of the results with other existing statistical distributions. The result shows that the Exponential Gamma distribution is adequate and also performed better than the existing distributions. Ayeni Taiwo Michael | Ogunwale Olukunle Daniel | Adewusi Oluwasesan Adeoye ""Application of Exponential-Gamma Distribution in Modeling Queuing Data"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd30097.pdf
Paper Url : https://www.ijtsrd.com/mathemetics/statistics/30097/application-of-exponential-gamma-distribution-in-modeling-queuing-data/ayeni-taiwo-michael
Advanced Survival Analysis
“Advanced Survival Analysis” is an online course offered at Statistics.com. Statistics.com is the leading provider of online education in statistics, and offers over 100 courses in introductory and advanced statistics. Courses typically are taught by leading experts. Some course highlights -
A. Taught by renowned International Faculty (Not self-paced learning)
B. Instructor led and Peer learning
C. Flexible and Convenient schedule
D. Practical Application and Software skills
For more details please contact info@c-elt.com.
Website: www.india.statistics.com
Time To Practice Week 3
The document discusses an investigation into how two marine invertebrates, the shore crab (Carcinus maenas) and lugworm (Arenicola marina), regulate their bodily fluid concentrations in response to varying salinity levels in seawater. The study found that C. maenas was able to maintain a constant internal osmolarity despite changes in external salinity, demonstrating it is an osmoregulator. In contrast, A. marina's internal osmolarity matched changes in external salinity, showing it is an osmoconformer. The results provide insight into the differing osmoregulatory abilities of marine invertebrates under changing environmental conditions.
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Extending the Gillespie's Stochastic Simulation Algorithm for Integrating Dis...
Whereas Multi-Agent Based Simulation (MABS) is emerging as a reference approach for complex system simulation, the event-driven approach of Discrete-Event Simulation (DES) is the most used approach in the simulation mainstream.
In this talk, we elaborate on two intuitions: 1) event-based systems and multi-agent systems are amenable of a coherent interpretation within a unique conceptual framework; 2) integrating MABS and DES can lead to a more expressive and powerful simulation framework.
Accordingly, we propose a computational model integrating DES and MABS, based on an extension of the Gillespie's stochastic simulation algorithm.
Then, we discuss a case of a simulation platform (Alchemist) specifically targeted at such a kind of complex models, and show an example of urban crowd steering simulation.
Applying Genetic Algorithms to Information Retrieval Using Vector Space Model
Genetic algorithms are usually used in information retrieval systems (IRs) to enhance the information retrieval process, and to increase the efficiency of the optimal information retrieval in order to meet the users’ needs and help them find what they want exactly among the growing numbers of available information. The improvement of adaptive genetic algorithms helps to retrieve the information needed by the user accurately, reduces the retrieved relevant files and excludes irrelevant files. In this study, the researcher explored the problems embedded in this process, attempted to find solutions such as the way of choosing mutation probability and fitness function, and chose Cranfield English Corpus test collection on mathematics. Such collection was conducted by Cyrial Cleverdon and used at the University of Cranfield in 1960 containing 1400 documents, and 225 queries for simulation purposes. The researcher also used cosine similarity and jaccards to compute similarity between the query and documents, and used two proposed adaptive fitness function, mutation operators as well as adaptive crossover. The process aimed at evaluating the effectiveness of results according to the measures of precision and recall. Finally, the study concluded that we might have several improvements when using adaptive genetic algorithms.
Recommending Sequences RecTour 2017
This document presents a framework for recommending personalized sequences of activities to users in the tourism domain. It discusses using sequential user activity data with associated contextual features like location and time. The framework extends previous work on single-activity recommendations by recommending a sequence of activities. It models user activity timelines and candidate timelines, calculates similarity between them, ranks candidates, and iteratively recommends the next activity sequences. It applies this approach to a location check-in dataset, finding the sequence recommendation algorithm outperforms baselines at predicting user activity sequences.
KatKennedy REU D.C. Poster
The AP-CAT project aims to develop an adaptive computerized test for AP Statistics that assesses student mastery of specific statistical concepts and provides formative feedback. Researchers are investigating whether use of the adaptive test promotes student engagement and improves learning outcomes. A survey found positive correlations between use of the AP-CAT system and different types of student engagement. The project is in its third year of a five-year study, and future work will explore causality and expand validation and diversity of the student sample.
Dynamic Symbolic Database Application Testing
Dynamic Symbolic Database Application TestingThe Innovative Data Intelligence Research (IDIR) Laboratory, University of Texas at Arlington
A database application differs form regular applications in that some of its inputs may be database queries. The program will execute the queries on a database and may use any result values in its subsequent program logic. This means that a user-supplied query may determine the values that the application will use in subsequent branching conditions. At the same time, a new database application is often required to work well on a body of existing data stored in some large database. For systematic testing of database applications, recent techniques replace the existing database with carefully crafted mock databases. Mock databases return values that will trigger as many execution paths in the application as possible and thereby maximize overall code coverage of the database application.
In this paper we offer an alternative approach to database application testing. Our goal is to support software engineers in focusing testing on the existing body of data the application is required to work well on. For that, we propose to side-step mock database generation and instead generate queries for the existing database. Our key insight is that we can use the information collected during previous program executions to systematically generate new queries that will maximize the coverage of the application under test, while guaranteeing that the generated test cases focus on the existing data.Similar to mFPCA (20)
Treatment of Steel Rolling Mill Effluents Using Semi-Batch Foam Flotation
Treatment of Steel Rolling Mill Effluents Using Semi-Batch Foam Flotation
Hybrid model in machine learning–robust regression applied for sustainabilit...
Hybrid model in machine learning–robust regression applied for sustainabilit...
Social networks, activities, and travel - building links to understand behaviour
Social networks, activities, and travel - building links to understand behaviour
A Tree-Based Approach for Addressing Self-Selection in Impact Studies with Bi...
A Tree-Based Approach for Addressing Self-Selection in Impact Studies with Bi...
Simultaneous Optimization of Mean andStandard DeviationN.docx
Simultaneous Optimization of Mean andStandard DeviationN.docx
1PPA 670 Public Policy AnalysisBasic Policy Terms an.docx
1PPA 670 Public Policy AnalysisBasic Policy Terms an.docx
Ensemble Filters to Reduce Uncertanties in San Quintin Bay Hidrodynamic System
Ensemble Filters to Reduce Uncertanties in San Quintin Bay Hidrodynamic System
Application of Exponential Gamma Distribution in Modeling Queuing Data
Application of Exponential Gamma Distribution in Modeling Queuing Data
Extending the Gillespie's Stochastic Simulation Algorithm for Integrating Dis...
Extending the Gillespie's Stochastic Simulation Algorithm for Integrating Dis...
Applying Genetic Algorithms to Information Retrieval Using Vector Space Model
Applying Genetic Algorithms to Information Retrieval Using Vector Space Model
More from Kevin Cummins
D&I Presentation
This document proposes a mixed methods study to identify barriers and strategies to implementing personalized normative feedback (PNF) interventions for reducing alcohol use on U.S. college campuses. The study has two aims: 1) Use interviews and surveys to identify determinants of and strategies for PNF implementation. 2) Experimentally evaluate implementation strategies, such as developing educational materials, to increase adoption and sustainability of PNF on college campuses. The study would involve qualitative interviews followed by surveys of college administrators, then a randomized trial of 84 colleges to test the strategies. Outcome measures would assess acceptability, adoption, appropriateness and sustainability of PNF. The goal is to expand evidence-based solutions to reduce harms of college
Ncd.mobileappdev
The document discusses plans to develop a mobile app for the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study. The app aims to enhance characterization of substance use patterns, obtain ecological momentary assessments of affect, and allow for frequent low-burden micro-assessments across multiple domains. A team including a mobile app developer, interface developer, and backend programmer will develop the app to be compatible with iOS and Android, securely store data even without network connectivity, and use multiple randomized assessment schedules with simple, quick 10-second surveys. Proposed assessments include monthly substance use, bi-weekly sleep, exercise and activities reporting and substance use/problems, and daily affect and craving surveys.
Bayesian Model for Multivatiate Functional Principle Components Analysis
Kevin Cummins
Joint Doctoral Program in Interdisciplinary Research on Substance Use
University of California, San Diego
JSM Digital Poster Presentation, August 2015
Kevin Cummins' Botany Sampler
This document summarizes a presentation on plant structure and function given to the California Rare Fruit Growers. It discusses how plants are modular organisms with indeterminate growth, and outlines key topics covered including plant cells, stem and leaf structure, photosynthesis, root structure, transport within plants, and flowers and fruit. It provides diagrams and descriptions of topics like epidermal and vascular tissue, growth patterns, chloroplasts and photosynthesis, root architecture, water and sugar transport, and seed dispersal.
To Burn Or Not To Burn: Using Population Models to Address the Management Cha...
Dynamic spatial modeling in southern California shurblands. Kevin Cummins, Dawn Lawson, Keith Lombardo.
Regression to the Mean, Kevin Cummins, Addictions Seminar, UCSD
Regression to the mean is a statistical phenomenon where extreme values are likely to be closer to the average upon subsequent measurements. In addiction research, it can cause mistaken conclusions that changes in outcomes are due to treatment when they are actually due to random fluctuations. Researchers should minimize measurement error, use comparison groups, statistical corrections, and make reasonable conclusions about the effects of regression to the mean.
San diego sunshine law kevin cummins
Suggested discussion points for the Encinitas Project Forum on municipal public policy, by Kevin Cummins.
More from Kevin Cummins (7)
Bayesian Model for Multivatiate Functional Principle Components Analysis
Bayesian Model for Multivatiate Functional Principle Components Analysis
To Burn Or Not To Burn: Using Population Models to Address the Management Cha...
To Burn Or Not To Burn: Using Population Models to Address the Management Cha...
Regression to the Mean, Kevin Cummins, Addictions Seminar, UCSD
Regression to the Mean, Kevin Cummins, Addictions Seminar, UCSD
Recently uploaded
Nucleic Acid-its structural and functional complexity.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/SAR of Medicinal Chemistry 1st by dk.pdf
In this presentation include the prototype drug SAR on thus or with their examples .
Syllabus of Second Year B. Pharmacy
2019 PATTERN.
Deep Software Variability and Frictionless Reproducibility
Deep Software Variability and Frictionless ReproducibilityUniversity of Rennes, INSA Rennes, Inria/IRISA, CNRS
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
Shallowest Oil Discovery of Turkiye.pptx
The Petroleum System of the Çukurova Field - the Shallowest Oil Discovery of Türkiye, Adana
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
Context. With a mass exceeding several 104 M⊙ and a rich and dense population of massive stars, supermassive young star clusters
represent the most massive star-forming environment that is dominated by the feedback from massive stars and gravitational interactions
among stars.
Aims. In this paper we present the Extended Westerlund 1 and 2 Open Clusters Survey (EWOCS) project, which aims to investigate
the influence of the starburst environment on the formation of stars and planets, and on the evolution of both low and high mass stars.
The primary targets of this project are Westerlund 1 and 2, the closest supermassive star clusters to the Sun.
Methods. The project is based primarily on recent observations conducted with the Chandra and JWST observatories. Specifically,
the Chandra survey of Westerlund 1 consists of 36 new ACIS-I observations, nearly co-pointed, for a total exposure time of 1 Msec.
Additionally, we included 8 archival Chandra/ACIS-S observations. This paper presents the resulting catalog of X-ray sources within
and around Westerlund 1. Sources were detected by combining various existing methods, and photon extraction and source validation
were carried out using the ACIS-Extract software.
Results. The EWOCS X-ray catalog comprises 5963 validated sources out of the 9420 initially provided to ACIS-Extract, reaching a
photon flux threshold of approximately 2 × 10−8 photons cm−2
s
−1
. The X-ray sources exhibit a highly concentrated spatial distribution,
with 1075 sources located within the central 1 arcmin. We have successfully detected X-ray emissions from 126 out of the 166 known
massive stars of the cluster, and we have collected over 71 000 photons from the magnetar CXO J164710.20-455217.
The debris of the ‘last major merger’ is dynamically young
The Milky Way’s (MW) inner stellar halo contains an [Fe/H]-rich component with highly eccentric orbits, often referred to as the
‘last major merger.’ Hypotheses for the origin of this component include Gaia-Sausage/Enceladus (GSE), where the progenitor
collided with the MW proto-disc 8–11 Gyr ago, and the Virgo Radial Merger (VRM), where the progenitor collided with the
MW disc within the last 3 Gyr. These two scenarios make different predictions about observable structure in local phase space,
because the morphology of debris depends on how long it has had to phase mix. The recently identified phase-space folds in Gaia
DR3 have positive caustic velocities, making them fundamentally different than the phase-mixed chevrons found in simulations
at late times. Roughly 20 per cent of the stars in the prograde local stellar halo are associated with the observed caustics. Based
on a simple phase-mixing model, the observed number of caustics are consistent with a merger that occurred 1–2 Gyr ago.
We also compare the observed phase-space distribution to FIRE-2 Latte simulations of GSE-like mergers, using a quantitative
measurement of phase mixing (2D causticality). The observed local phase-space distribution best matches the simulated data
1–2 Gyr after collision, and certainly not later than 3 Gyr. This is further evidence that the progenitor of the ‘last major merger’
did not collide with the MW proto-disc at early times, as is thought for the GSE, but instead collided with the MW disc within
the last few Gyr, consistent with the body of work surrounding the VRM.
Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...
The pygmy halfbeak Dermogenys colletei, is known for its viviparous nature, this presents an intriguing case of relatively low fecundity, raising questions about potential compensatory reproductive strategies employed by this species. Our study delves into the examination of fecundity and the Gonadosomatic Index (GSI) in the Pygmy Halfbeak, D. colletei (Meisner, 2001), an intriguing viviparous fish indigenous to Sarawak, Borneo. We hypothesize that the Pygmy halfbeak, D. colletei, may exhibit unique reproductive adaptations to offset its low fecundity, thus enhancing its survival and fitness. To address this, we conducted a comprehensive study utilizing 28 mature female specimens of D. colletei, carefully measuring fecundity and GSI to shed light on the reproductive adaptations of this species. Our findings reveal that D. colletei indeed exhibits low fecundity, with a mean of 16.76 ± 2.01, and a mean GSI of 12.83 ± 1.27, providing crucial insights into the reproductive mechanisms at play in this species. These results underscore the existence of unique reproductive strategies in D. colletei, enabling its adaptation and persistence in Borneo's diverse aquatic ecosystems, and call for further ecological research to elucidate these mechanisms. This study lends to a better understanding of viviparous fish in Borneo and contributes to the broader field of aquatic ecology, enhancing our knowledge of species adaptations to unique ecological challenges.
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8.Isolation of pure cultures and preservation of cultures.pdf
Isolation of pure culture, its various method.
bordetella pertussis.................................ppt
Bordettela is a gram negative cocobacilli spread by air born drop let
Nucleophilic Addition of carbonyl compounds.pptx
Nucleophilic addition is the most important reaction of carbonyls. Not just aldehydes and ketones, but also carboxylic acid derivatives in general.
Carbonyls undergo addition reactions with a large range of nucleophiles.
Comparing the relative basicity of the nucleophile and the product is extremely helpful in determining how reversible the addition reaction is. Reactions with Grignards and hydrides are irreversible. Reactions with weak bases like halides and carboxylates generally don’t happen.
Electronic effects (inductive effects, electron donation) have a large impact on reactivity.
Large groups adjacent to the carbonyl will slow the rate of reaction.
Neutral nucleophiles can also add to carbonyls, although their additions are generally slower and more reversible. Acid catalysis is sometimes employed to increase the rate of addition.
Sharlene Leurig - Enabling Onsite Water Use with Net Zero Water
Sharlene Leurig - Enabling Onsite Water Use with Net Zero WaterTexas Alliance of Groundwater Districts
Presented at June 6-7 Texas Alliance of Groundwater Districts Business MeetingRemote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...University of Maribor
Slides from talk:
Aleš Zamuda: Remote Sensing and Computational, Evolutionary, Supercomputing, and Intelligent Systems.
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Inter-Society Networking Panel GRSS/MTT-S/CIS Panel Session: Promoting Connection and Cooperation
https://www.etran.rs/2024/en/home-english/Travis Hills' Endeavors in Minnesota: Fostering Environmental and Economic Pr...
Travis Hills of Minnesota developed a method to convert waste into high-value dry fertilizer, significantly enriching soil quality. By providing farmers with a valuable resource derived from waste, Travis Hills helps enhance farm profitability while promoting environmental stewardship. Travis Hills' sustainable practices lead to cost savings and increased revenue for farmers by improving resource efficiency and reducing waste.
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Nucleic Acid-its structural and functional complexity.
Nucleic Acid-its structural and functional complexity.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...
Deep Software Variability and Frictionless Reproducibility
Deep Software Variability and Frictionless Reproducibility
mô tả các thí nghiệm về đánh giá tác động dòng khí hóa sau đốt
mô tả các thí nghiệm về đánh giá tác động dòng khí hóa sau đốt
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
The debris of the ‘last major merger’ is dynamically young
The debris of the ‘last major merger’ is dynamically young
Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...
Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...
8.Isolation of pure cultures and preservation of cultures.pdf
8.Isolation of pure cultures and preservation of cultures.pdf
bordetella pertussis.................................ppt
bordetella pertussis.................................ppt
Sharlene Leurig - Enabling Onsite Water Use with Net Zero Water
Sharlene Leurig - Enabling Onsite Water Use with Net Zero Water
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...
Travis Hills' Endeavors in Minnesota: Fostering Environmental and Economic Pr...
Travis Hills' Endeavors in Minnesota: Fostering Environmental and Economic Pr...
mFPCA
- 1. Introduction The Model Application Multivariate Functional Principal Components Analysis (mFPCA) Kevin Cummins Joint Doctoral Program in Interdisciplinary Research in Substance Use Division of Global Public Health University of California, San Diego Department of Social Work San Diego State University Wes Thompson Department of Psychiatry University of California, San Diego August 9, 2015 Kevin Cummins JSM 2015v1
- 2. Introduction The Model Application Multivariate Functional Principal Component Analysis FPCA is a technique for estimating individual (smooth) trajectories from sparse longitudinal data (James, Hastie, & Sugar 2000) Goals: Estimate smooth mean trajectory, Determine smooth principal modes of variation of trajectories around mean levels. mFPCA is a technique to simultaneously estimation trajectories of multiple processes. Added Goals: Evaluate the association in the modes of variation among the processes. Kevin Cummins JSM 2015v1
- 3. Introduction The Model Application Functional PCA model The response of individual i at time t is multivariate and modeled as Yi(tij) = fi(tij) + ij = µ(tij) + hi(tij) + ij = φT (tij)θµ + φT (tij)Θαi + ij φ(t) = (φ1(t), φ2(t), . . . , φK (t)): K-dimensional vector of orthogonal basis functions evaluated at time tij. θµ: K-dimensional vector of basis coefficients. Kevin Cummins JSM 2015v1
- 4. Introduction The Model Application Multivariate Functional Principal Component Analysis (mFPCA) The response of individual i at time t is multivariate and modeled as Yi(t) = ΦT (t)θµ + ΦT (t)Θαi + i(t) Yi(t): P-dimensional observed response at time t φ(t) = (φ1(t), φ2(t), . . . , φK (t))T : K-dimensional vector of orthogonal basis functions evaluated at time tij and ΦT (t) = φT (t) . . . 0T ... ... ... 0T . . . φT (t) Θp: K by Qp matrix of spline coefficients subject to ΘT p Θp = I and Θ = Θ1 . . . 0 ... ... ... 0T . . . ΘP Kevin Cummins JSM 2015v1
- 5. Introduction The Model Application Brain Region Trajectories Kevin Cummins JSM 2015v1
- 6. Introduction The Model Application Modes of Variation Kevin Cummins JSM 2015v1