Bayesian nonparametric analysis of stock–recruitment relationships

2005 ◽  
Vol 62 (8) ◽  
pp. 1808-1821 ◽  
Author(s):  
Stephan B Munch ◽  
Athanasios Kottas ◽  
Marc Mangel
Keyword(s):  
Parametric Model ◽  
Reference Points ◽  
Parametric Models ◽  
Biological Information ◽  
Data Sets ◽  
Bayesian Nonparametric ◽  
Nonparametric Approach ◽  
Ophiodon Elongatus ◽  
Stock Recruitment ◽  
The Relationship

The relationship between current abundance and future recruitment to the stock is fundamental to managing fish populations. However, many different recruitment models are plausible and the data are insufficient to distinguish among them. Although nonparametric methods may be used to circumvent this problem, these are devoid of biological underpinnings. Here, we present a Bayesian nonparametric approach that allows straightforward incorporation of prior biological information and use it to estimate several fishery reference points. We applied this method to artificial data sets generated from a variety of parametric models and compare the results with the fit of Ricker and Beverton–Holt models. We found that the Bayesian nonparametric method fit the data nearly as well as the true parametric model and always performed better than incorrect parametric alternatives. The estimated reference points agree closely with true values calculated for the underlying parametric model. Finally, we apply the method to empirical data for lingcod (Ophiodon elongatus) and several salmonids. Since this method is capable of reproducing the behavior of any of the parametric models and provides flexible, data-driven estimates of stock–recruitment relationships, it should be of great value in fisheries applications where the true functional relationship is always unknown.

A Nonparametric Approach to Generating Inseason Forecasts of Salmon Returns

1989 ◽  
Vol 46 (12) ◽  
pp. 2046-2055 ◽  
Author(s):  
D. J. Noakes
Keyword(s):  
Sockeye Salmon ◽  
Ad Hoc ◽  
Parametric Models ◽  
Probability Density Estimation ◽  
Nonparametric Approach ◽  
Conditional Expectations ◽  
Skeena River ◽  
Changes Over Time ◽  
The Relationship ◽  
Quantities Of Interest

Variations in the size and timing of salmon runs have frustrated attempts to develop models for updating forecasts of returns inseason. The relationship between run size and inseason predictor variables is often nonlinear and changes over time. The nature of these nonlinearities is generally not known and analysts have elected to approximate observed patterns in the data with ad hoc parametric models. Although conceptually attractive, the performance of these models is frequently degraded by their inflexibility and failure to satisfy key model assumptions. In this paper, nonparametric probability density estimation techniques are employed to calculate the total run size conditional on the observed inseason data. Unlike the parametric techniques, the nonparametric approach allows the data to speak for themselves instead of having to merely conform to some arbitrary mathematical model. The approach is easily adapted to handle information from either terminal or guantlet fisheries and can be generalized to compute conditional expectations of various quantities of interest including run size, run timing, or both. Weekly estimates of the number of sockeye salmon (Oncorhynchus nerka) returning to the Skeena River, British Columbia, are employed to demonstrate the performance of the model.

Bayesian Nonparametric Approach to Credibility Modelling

2007 ◽  
Vol 2 (1) ◽  
pp. 91-114 ◽  
Author(s):  
A. Gangopadhyay ◽  
W.-C. Gau
Keyword(s):  
High Speed ◽  
Covariance Structure ◽  
Predictive Distribution ◽  
Parametric Models ◽  
Credibility Theory ◽  
Bayesian Nonparametric ◽  
Nonparametric Approach ◽  
Covariate Information ◽  
Software Packages ◽  
Modelling Strategies

ABSTRACTCurrent methods in credibility theory often rely on parametric models, e.g., a linear function of past experience. During the last decade, the existence of high speed computers and statistical software packages allowed the introduction of more sophisticated and flexible modelling strategies. In recent years, some of these techniques, which made use of the Markov Chain Monte Carlo (MCMC) approach to modelling, have been incorporated in credibility theory. However, very few of these methods made use of additional covariate information related to risk, or collection of risks; and at the same time account for the correlated structure in the data. In this paper, we consider a Bayesian nonparametric approach to the problem of risk modelling. The model incorporates past and present observations related to risk, as well as relevant covariate information. This Bayesian modelling is carried out by sampling from a multivariate Gaussian prior, where the covariance structure is based on a thin-plate spline. The model uses the MCMC technique to compute the predictive distribution of future claims based on available data.

scholarly journals Label-Sensitive Task Grouping by Bayesian Nonparametric Approach for Multi-Task Multi-Label Learning

2018 ◽  
Author(s):  
Xiao Zhang ◽  
Wenzhong Li ◽  
Vu Nguyen ◽  
Fuzhen Zhuang ◽  
Hui Xiong ◽  
...  
Keyword(s):  
Gene Annotation ◽  
Model Performance ◽  
Shared Knowledge ◽  
Data Sets ◽  
Bayesian Nonparametric ◽  
Learning Models ◽  
Learning Problem ◽  
Nonparametric Approach ◽  
Real World Applications ◽  
Label Correlations

Multi-label learning is widely applied in many real-world applications, such as image and gene annotation. While most of the existing multi-label learning models focus on the single-task learning problem, there are always some tasks that share some commonalities, which can help each other to improve the learning performances if the knowledge in the similar tasks can be smartly shared. In this paper, we propose a LABel-sensitive TAsk Grouping framework, named LABTAG, based on Bayesian nonparametric approach for multi-task multi-label classification. The proposed framework explores the label correlations to capture feature-label patterns, and clusters similar tasks into groups with shared knowledge, which are learned jointly to produce a strengthened multi-task multi-label model. We evaluate the model performance on three public multi-task multi-label data sets, and the results show that LABTAG outperforms the compared baselines with a significant margin.

scholarly journals Fitting a non-parametric stock–recruitment model in R that is useful for deriving MSY reference points and accounting for model uncertainty

2012 ◽  
Vol 70 (1) ◽  
pp. 56-67 ◽  
Author(s):  
Noel G. Cadigan
Keyword(s):  
Confidence Intervals ◽  
Model Uncertainty ◽  
Fishery Management ◽  
Reference Points ◽  
Parametric Models ◽  
Parametric Approach ◽  
Stock Size ◽  
Stock Recruitment ◽  
Recruitment Model ◽  
Non Parametric

Abstract Cadigan, N. G. 2013. Fitting a non-parametric stock–recruitment model in R that is useful for deriving MSY reference points and accounting for model uncertainty. – ICES Journal of Marine Science, 70:56–67. Modelling the relationship between parental stock size and subsequent recruitment of fish to a fishery is often required when deriving reference points, which are a fundamental component of fishery management. A non-parametric approach to estimate stock–recruitment relationships is illustrated using a simulated example and nine case studies. The approach preserves compensatory density dependence in which the recruitment rate monotonically decreases as stock size increases, which is a basic assumption of commonly used parametric stock–recruitment models. The implications of the non-parametric estimates on maximum sustainable yield (MSY) reference points are illustrated. The approach is used to provide non-parametric bootstrapped confidence intervals for reference points. The efficacy of the approach is investigated using simulations. The results demonstrate that the non-parametric approach can provide a more realistic estimation of the stock–recruitment relationship when informative data are available compared with common parametric models. Also, bootstrap confidence intervals for MSY reference points based on different parametric stock–recruitment models often do not overlap. The confidence intervals based on the non-parametric approach tend to be much wider, and reflect better uncertainty due to stock–recruit model choice.

The visual arrays task…visual storage capacity or attention control?

2019 ◽  
Author(s):  
Jessie Martin ◽  
Jason S. Tsukahara ◽  
Christopher Draheim ◽  
Zach Shipstead ◽  
Cody Mashburn ◽  
...  
Keyword(s):  
Working Memory ◽  
Storage Capacity ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Attention Control ◽  
Data Sets ◽  
Independent Data ◽  
Visual Storage ◽  
Design Selection ◽  
The Relationship

**The uploaded manuscript is still in preparation** In this study, we tested the relationship between visual arrays tasks and working memory capacity and attention control. Specifically, we tested whether task design (selection or non-selection demands) impacted the relationship between visual arrays measures and constructs of working memory capacity and attention control. Using analyses from 4 independent data sets we showed that the degree to which visual arrays measures rely on selection influences the degree to which they reflect domain-general attention control.

Structural-parametric model of an electroelastic actuator for nanomechanics

2020 ◽  
pp. 3-11
Author(s):  
S.M. Afonin
Keyword(s):  
Transfer Function ◽  
Piezoelectric Actuator ◽  
Transfer Functions ◽  
Piezoelectric Effect ◽  
Parametric Model ◽  
Elastic Compliance ◽  
Parametric Models ◽  
Piezo Actuator ◽  
Structural Scheme ◽  
Model Transfer

Structural-parametric models, structural schemes are constructed and the transfer functions of electro-elastic actuators for nanomechanics are determined. The transfer functions of the piezoelectric actuator with the generalized piezoelectric effect are obtained. The changes in the elastic compliance and rigidity of the piezoactuator are determined taking into account the type of control. Keywords electro-elastic actuator, piezo actuator, structural-parametric model, transfer function, parametric structural scheme

Epidemiological Evidence that Maternal Influenza Contributes to the Aetiology of Schizophrenia

1993 ◽  
Vol 163 (4) ◽  
pp. 522-534 ◽  
Author(s):  
W. Adams ◽  
R. E. Kendell ◽  
E. H. Hare ◽  
P. Munk-Jørgensen
Keyword(s):  
Data Sets ◽  
Time Lags ◽  
Epidemiological Evidence ◽  
Intrauterine Development ◽  
Increased Risk ◽  
Schizophrenic Patients ◽  
The Relationship ◽  
Monthly Incidence ◽  
Maternal Influenza

The epidemiological evidence that the offspring of women exposed to influenza in pregnancy are at increased risk of schizophrenia is conflicting. In an attempt to clarify the issue we explored the relationship between the monthly incidence of influenza (and measles) in the general population and the distribution of birth dates of three large series of schizophrenic patients - 16 960 Scottish patients born in 1932–60; 22 021 English patients born in 1921–60; and 18 723 Danish patients born in 1911–65. Exposure to the 1957 epidemic of A2 influenza in midpregnancy was associated with an increased incidence of schizophrenia, at least in females, in all three data sets. We also confirmed the previous report of a statistically significant long-term relationship between patients' birth dates and outbreaks of influenza in the English series, with time lags of - 2 and - 3 months (the sixth and seventh months of pregnancy). Despite several other negative studies by ourselves and others we conclude that these relationships are probably both genuine and causal; and that maternal influenza during the middle third of intrauterine development, or something closely associated with it, is implicated in the aetiology of some cases of schizophrenia.

scholarly journals Determination of vertical dimension of occlusion by using the phonetic vowel "O" and "E"

2015 ◽  
Vol 72 (2) ◽  
pp. 123-131 ◽  
Author(s):  
Marko Igic ◽  
Nebojsa Krunic ◽  
Ljiljana Aleksov ◽  
Milena Kostic ◽  
Aleksandra Igic ◽  
...  
Keyword(s):  
Cognitive Functions ◽  
Complete Denture ◽  
Reference Points ◽  
Vertical Dimension ◽  
Entire Sample ◽  
Average Value ◽  
Significant Difference ◽  
The Relationship

Background/Aim. The vertical dimension of occlusion is a very important parameter for proper reconstruction of the relationship between the jaws. The literature describes many methods for its finding, from the simple, easily applicable clinically, to quite complicated, with the use of one or more devices for determination. The aim of this study was to examine the possibility of determining the vertical dimension of occlusion using the vocals ?O? and ?E? with the control of values o btained by applying cognitive functions. Methods. This investigation was performed with the two groups of patients. The first group consisted of 50 females and 50 males, aged 18 to 30 years. In this group the distance between the reference points (on top of the nose and chin) was measured in the position of the mandible in the vertical dimension of occlusion, the vertical dimension at rest and the pronunciation of the words ?OLO? and ?ELE?. Checking the correctness of the particular value for the word ?OLO? was also performed by the phonetic method with the application of cognitive exercises when the patients counted from 89 to 80. The obtained difference in the average values i n determining the vertical dimension of occlusion and the ?OLO? and ?ELE? in the first group was used as the reference for determining the vertical dimension of occlusion in the second group of patients. The second group comprised of 31 edentulous persons (14 females and 17 males), aged from 54 to 85 years who had been made a complete denture. Results. The average value obtained for the vertical dimension of rest for the entire sample was 2.16 mm, for the word ?OLO? for the entire sample was 5.51 mm and for the word ?ELE? for the entire sample was 7.47 mm. There was no statistically significant difference between the genders for the value of the vertical dimension at rest, ?ELE? and ?OLO?. There was a statistically significant difference between the values f or the vertical dimension at rest, ?OLO? and ?ELE? for both genders. There was a statistically significant correlation between the value for the vertical dimension at rest, ?OLO? and ?ELE?, for both groups of subjects. Conclusion. Determining the vertical dimension of occlusion requires 5.5 mm subtraction from the position of the mandible in pronunciation of the word ?OLO? or 7.5 mm in pronunciation of the word ?ELE?.

PSVI-8 Meta-regression Analysis to Determine the Relationship Between Growing Pig Body Weight and Variation

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 218-219
Author(s):  
Andres Fernando T Russi ◽  
Mike D Tokach ◽  
Jason C Woodworth ◽  
Joel M DeRouchey ◽  
Robert D Goodband ◽  
...  
Keyword(s):  
Body Weight ◽  
Regression Analysis ◽  
Sample Size ◽  
Polynomial Regression ◽  
Data Sets ◽  
Regression Equations ◽  
Prediction Equations ◽  
Data Set ◽  
Rate Of Increase ◽  
The Relationship

Abstract The swine industry has been constantly evolving to select animals with improved performance traits and to minimize variation in body weight (BW) in order to meet packer specifications. Therefore, understanding variation presents an opportunity for producers to find strategies that could help reduce, manage, or deal with variation of pigs in a barn. A systematic review and meta-analysis was conducted by collecting data from multiple studies and available data sets in order to develop prediction equations for coefficient of variation (CV) and standard deviation (SD) as a function of BW. Information regarding BW variation from 16 papers was recorded to provide approximately 204 data points. Together, these data included 117,268 individually weighed pigs with a sample size that ranged from 104 to 4,108 pigs. A random-effects model with study used as a random effect was developed. Observations were weighted using sample size as an estimate for precision on the analysis, where larger data sets accounted for increased accuracy in the model. Regression equations were developed using the nlme package of R to determine the relationship between BW and its variation. Polynomial regression analysis was conducted separately for each variation measurement. When CV was reported in the data set, SD was calculated and vice versa. The resulting prediction equations were: CV (%) = 20.04 – 0.135 × (BW) + 0.00043 × (BW)2, R2=0.79; SD = 0.41 + 0.150 × (BW) - 0.00041 × (BW)2, R2 = 0.95. These equations suggest that there is evidence for a decreasing quadratic relationship between mean CV of a population and BW of pigs whereby the rate of decrease is smaller as mean pig BW increases from birth to market. Conversely, the rate of increase of SD of a population of pigs is smaller as mean pig BW increases from birth to market.

scholarly journals Dampness and student-reported social climate: two multilevel mediation models

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Eerika Finell ◽  
Asko Tolvanen ◽  
Juha Pekkanen ◽  
Timo Ståhl ◽  
Pauliina Luopa
Keyword(s):  
Indoor Air ◽  
Social Climate ◽  
School Level ◽  
Data Sets ◽  
Student Relationships ◽  
Teacher Student Relationships ◽  
Teacher Student ◽  
Mediational Models ◽  
The Relationship ◽  
Perceptions Of School

Abstract Background Little previous research has analysed the relationship between schools’ indoor air problems and schools’ social climate. In this study, we analysed a) whether observed mould and dampness in a school building relates to students’ perceptions of school climate (i.e. teacher-student relationships and class spirit) and b) whether reported subjective indoor air quality (IAQ) at the school level mediates this relationship. Methods The data analysed was created by merging two nationwide data sets: survey data from students, including information on subjective IAQ (N = 25,101 students), and data from schools, including information on mould and dampness in school buildings (N = 222). The data was analysed using multilevel mediational models. Results After the background variables were adjusted, schools’ observed mould and dampness was not significantly related to neither student-perceived teacher-student relationships nor class spirit. However, our mediational models showed that there were significant indirect effects from schools’ observed mould and dampness to outcome variables via school-level subjective IAQ: a) in schools with mould and dampness, students reported significantly poorer subjective IAQ (standardised β = 0.34, p < 0.001) than in schools without; b) the worse the subjective IAQ at school level, the worse the student-reported teacher-student relationships (β = 0.31, p = 0.001) and class spirit (β = 0.25, p = 0.006). Conclusions Problems in a school’s indoor environment may impair the school’s social climate to the degree that such problems decrease the school’s perceived IAQ.

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