scholarly journals Model Tuning with Canonical Correlation Analysis

2014 ◽  
Vol 142 (5) ◽  
pp. 2018-2027 ◽  
Author(s):  
Caren Marzban ◽  
Scott Sandgathe ◽  
James D. Doyle
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Convective Precipitation ◽  
Model Parameters ◽  
Prediction System ◽  
Multivariate Statistical ◽  
The Difference ◽  
Model Tuning ◽  
The Relationship

Abstract Knowledge of the relationship between model parameters and forecast quantities is useful because it can aid in setting the values of the former for the purpose of having a desired effect on the latter. Here it is proposed that a well-established multivariate statistical method known as canonical correlation analysis can be formulated to gauge the strength of that relationship. The method is applied to several model parameters in the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) for the purpose of “controlling” three forecast quantities: 1) convective precipitation, 2) stable precipitation, and 3) snow. It is shown that the model parameters employed here can be set to affect the sum, and the difference between convective and stable precipitation, while keeping snow mostly constant; a different combination of model parameters is shown to mostly affect the difference between stable precipitation and snow, with minimal effect on convective precipitation. In short, the proposed method cannot only capture the complex relationship between model parameters and forecast quantities, it can also be utilized to optimally control certain combinations of the latter.

Analysis of Maximum Expiratory Flow Volume Curves Using Canonical Correlation Analysis

1985 ◽  
Vol 24 (02) ◽  
pp. 91-100 ◽  
Author(s):  
W. van Pelt ◽  
Ph. H. Quanjer ◽  
M. E. Wise ◽  
E. van der Burg ◽  
R. van der Lende
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Flow Volume ◽  
Non Linear ◽  
Maximum Expiratory Flow ◽  
Expiratory Flow ◽  
Relationship Of ◽  
The Relationship ◽  
Age And Sex

SummaryAs part of a population study on chronic lung disease in the Netherlands, an investigation is made of the relationship of both age and sex with indices describing the maximum expiratory flow-volume (MEFV) curve. To determine the relationship, non-linear canonical correlation was used as realized in the computer program CANALS, a combination of ordinary canonical correlation analysis (CCA) and non-linear transformations of the variables. This method enhances the generality of the relationship to be found and has the advantage of showing the relative importance of categories or ranges within a variable with respect to that relationship. The above is exemplified by describing the relationship of age and sex with variables concerning respiratory symptoms and smoking habits. The analysis of age and sex with MEFV curve indices shows that non-linear canonical correlation analysis is an efficient tool in analysing size and shape of the MEFV curve and can be used to derive parameters concerning the whole curve.

The effectiveness of quality awards on the company's performance – the case of Iran's national quality awards

2020 ◽  
Vol 27 (4) ◽  
pp. 1319-1340
Author(s):  
Hossein Safari ◽  
Elham Razghandi ◽  
Mohammad Reza Fathi ◽  
Virgilio Cruz-Machado ◽  
Maria do Rosário Cabrita
Keyword(s):  
Logistic Regression ◽  
Correlation Analysis ◽  
Financial Performance ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Business Environment ◽  
Content Type ◽  
National Quality ◽  
Quality Awards ◽  
The Relationship

PurposeThe purpose of this study is to clarify the relationship between getting quality awards by companies and their financial performance in Iran's business.Design/methodology/approachIn the first step, the relationship between awards scores and financial performance by canonical correlation analysis was examined. Then, binary and multinomial logistic regression was used to determine the degree of impact of each financial performance measure on getting quality awards. Finally, two forecasting functions were explored: the probability of achieving quality awards and the probability of achieving different levels of these awards.FindingsBased on the analyzed data of 112 companies through canonical correlation analysis, there was a weak relationship between financial performance and getting quality awards. Also, by using logistic regression, no result was found to prove the impact of financial performance measures on getting Iran's national quality awards. It can be concluded that conceptually, deployment of excellence organizational models will not result in favorable outcomes, especially in the financial scope. Also, practically, excellence models have not been well deployed in Iranian companies, or these models do not fit to Iran's business environment. Organizational culture may not be consistent with quality.Originality/valueQuality awards are given to qualified companies following the establishment of models of excellence such as the European Foundation for Quality Management (EFQM). The main novelty of this research is to clarify the relationship between getting quality awards by companies and their financial performance in Iran's business.

scholarly journals Robust nonlinear canonical correlation analysis: application to seasonal climate forecasting

2008 ◽  
Vol 15 (1) ◽  
pp. 221-232 ◽  
Author(s):  
A. J. Cannon ◽  
W. W. Hsieh
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Mean Squared Error ◽  
Synthetic Dataset ◽  
Model Parameters ◽  
Inverse Mapping ◽  
Seasonal Climate ◽  
The Mean ◽  
Improved Performance

Abstract. Robust variants of nonlinear canonical correlation analysis (NLCCA) are introduced to improve performance on datasets with low signal-to-noise ratios, for example those encountered when making seasonal climate forecasts. The neural network model architecture of standard NLCCA is kept intact, but the cost functions used to set the model parameters are replaced with more robust variants. The Pearson product-moment correlation in the double-barreled network is replaced by the biweight midcorrelation, and the mean squared error (mse) in the inverse mapping networks can be replaced by the mean absolute error (mae). Robust variants of NLCCA are demonstrated on a synthetic dataset and are used to forecast sea surface temperatures in the tropical Pacific Ocean based on the sea level pressure field. Results suggest that adoption of the biweight midcorrelation can lead to improved performance, especially when a strong, common event exists in both predictor/predictand datasets. Replacing the mse by the mae leads to improved performance on the synthetic dataset, but not on the climate dataset except at the longest lead time, which suggests that the appropriate cost function for the inverse mapping networks is more problem dependent.

scholarly journals KERNEL MAD ALGORITHM FOR RELATIVE RADIOMETRIC NORMALIZATION

2016 ◽  
Vol III-1 ◽  
pp. 49-53 ◽  
Author(s):  
Yang Bai ◽  
Ping Tang ◽  
Changmiao Hu
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Landsat 8 ◽  
Linear Relationships ◽  
Multi Temporal ◽  
Kernel Canonical Correlation Analysis ◽  
The Difference ◽  
Complex Relationships ◽  
Beijing China

The multivariate alteration detection (MAD) algorithm is commonly used in relative radiometric normalization. This algorithm is based on linear canonical correlation analysis (CCA) which can analyze only linear relationships among bands. Therefore, we first introduce a new version of MAD in this study based on the established method known as kernel canonical correlation analysis (KCCA). The proposed method effectively extracts the non-linear and complex relationships among variables. We then conduct relative radiometric normalization experiments on both the linear CCA and KCCA version of the MAD algorithm with the use of Landsat-8 data of Beijing, China, and Gaofen-1(GF-1) data derived from South China. Finally, we analyze the difference between the two methods. Results show that the KCCA-based MAD can be satisfactorily applied to relative radiometric normalization, this algorithm can well describe the nonlinear relationship between multi-temporal images. This work is the first attempt to apply a KCCA-based MAD algorithm to relative radiometric normalization.

scholarly journals Investigating the relationship between gender inequality and happiness of OECD countries using classical and robust canonical correlation analysesOECD ülkelerinde cinsiyet eşitsizliği ve mutluluk arasindaki ilişkinin klasik ve dayanikli kanonik korelasyon analizleri ile incelenmesi

2016 ◽  
Vol 13 (3) ◽  
Author(s):  
Selay Giray ◽  
Özlem Yorulmaz ◽  
Bilge Başcı
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Gender Inequality ◽  
Canonical Correlation ◽  
Pearson Correlation ◽  
Oecd Countries ◽  
Equal Rights ◽  
Inequality Index ◽  
Political Empowerment ◽  
The Relationship

Gender equality corrresponds to equal rights and opportunities of individuals based on their gender. However, gender inequality refers mostly  lack of women’s  economic and political empowerment. Socially constructed different gender roles can be observed mostly in daily life.  Gender inequality  which can be perceived as an important social dynamic affects the happiness of individuals and hence  happiness of society. In this study, the relationship between the sub indicators of Gender Inequality Index and Happines Index for OECD countries have been investigated using canonical correlation analysis based on both pearson correlation matrix and  MM  covariance estimator. As is known, canonical correlation analysis explores the relationships between two multivariate sets of variables. Findings indicate that there is a strong correlation between Gender Inequality Index and Happines Index. ÖzetToplumsal cinsiyet eşitliği kadınların ve erkeklerin, kız ve erkek çocuklarının eşit hak, sorumluluk ve fırsatlardan yararlanma hakkına sahip oldukları anlamına gelmektedir. Daha çok kadına yönelik cinsiyet eşitsizliği olarak yansıyan cinsiyet eşitsizliği ise kaynaklara ve fırsatlara ulaşmada eşitsizlik, iş hayatı ve siyasette kadının sınırlı olarak yer alması şeklinde tanımlanabilir. Cinsiyet eşitsizliğinin gündelik yaşamdaki yansıması en iyi çiftler arasındaki ilişkilerde ve toplumsal kültürel yapıda gözlenebilmektedir. Toplumsal dinamik olarak önemli bir faktör olan cinsiyet eşitsizliği doğrudan bireylerin mutluluğu ve dolayısıyla toplumun mutluluğu üzerinde oldukça etkilidir. Bu çalışmada OECD ülkelerine ait Cinsiyet eşitsizliği indeksi bileşenleri  ve mutluluk indeksi bileşenleri arasındaki ilişki Pearson korelasyon matrisi ve dayanıklı (robust) MM kovaryans tahmincisine dayalı kanonik korelasyon analizleri ile incelenmiştir. Bilindiği gibi kanonik korelasyon analizi, değişken setleri arasındaki ilişki incelenirken kullanılan bir çok değişkenli analiz tekniğidir. Her iki yaklaşıma göre elde edilen bulgular mutluluk indeksi ve cinsiyet eşitsizliği indeksi arasında güçlü bir ilişkiye işaret etmektedir.

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