Statnote 32 : the partial correlation coefficient

In previous statnotes, the application of correlation and regression methods to the analysis of two variables (X,Y) was described. The most important statistic used to measure the degree of correlation between two variables is Pearson’s ‘product moment correlation coefficient’ (‘r’). The correlation between two variables may be due to their common relation to other variables. Hence, investigators using correlation studies need to be alert to the possibilities of spurious correlation and the methods of ‘partial correlation’ are one method of taking this into account. This statnote applies the methods of partial correlation to three scenarios. First, to a fairly obvious example of a spurious correlation resulting from the ‘size effect’ involving the relationship between the number of general practitioners (GP) and the number of deaths of patients in a town. Second, to the relationship between the abundance of the nitrogen-fixing bacterium Azotobacter in soil and three soil variables, and finally, to a more complex scenario, first introduced in Statnote 24involving the relationship between the growth of lichens in the field and climate.

Statnote 33:the intra-class correlation coefficient

The intra-class correlation coefficient (ICC or ri) is a method of measuring correlation when the data are paired and therefore, should be used when experimental units are organised into groups. A useful analogy is with the unpaired or paired ‘t’ test to compare the differences between the means of two groups. In studies of reproducibility, there may actually be little difference between the ICC and Pearson’s ‘r’ for ‘true’ repeated measurements. If, however, there is a systematic change in the measurements made on the first compared with the second occasion, then the ICC will be significantly less than ‘r’, and less confidence would be placed in the reproducibility of the results.

Semiparametric smooth-coefficient stochastic frontier model

This paper proposes a semiparametric smooth-coefficient (SPSC) stochastic production frontier model where regression coefficients are unknown smooth functions of environmental factors (ZZ). Technical inefficiency is specified in the form of a parametric scaling function which also depends on the ZZ variables. Thus, in our SPSC model the ZZ variables affect productivity directly via the technology parameters as well as through inefficiency. A residual-based bootstrap test of the relevance of the environmental factors in the SPSC model is suggested. An empirical application is also used to illustrate the technique.

Estimation of productivity in Korean electric power plants:a semiparametric smooth coefficient model

This paper analyzes the impact of load factor, facility and generator types on the productivity of Korean electric power plants. In order to capture important differences in the effect of load policy on power output, we use a semiparametric smooth coefficient (SPSC) model that allows us to model heterogeneous performances across power plants and over time by allowing underlying technologies to be heterogeneous. The SPSC model accommodates both continuous and discrete covariates. Various specification tests are conducted to compare performance of the SPSC model. Using a unique generator level panel dataset spanning the period 1995-2006, we find that the impact of load factor, generator and facility types on power generation varies substantially in terms of magnitude and significance across different plant characteristics. The results have strong implication for generation policy in Korea as outlined in this study.

Elemental partitioning and microstructural development in duplex stainless steel weld metal

A thermodynamic analysis which is capable of estimating the austenite/ferrite equilibria in duplex stainless steels has been carried out using the sublattice thermodynamic model. The partitioning of alloying elements between the austenite and ferrite phases has been calculated as a function of temperature. The results showed that chromium partitioning was not influenced significantly by the temperature. The molybdenum, on the other hand, was found to partition preferentially into ferrite phase as the temperature decreases. A strong partitioning of nickel into the austenite was observed to decrease gradually with increasing temperature. Among the alloying elements, average nitrogen concentration was found to have the most profound effect on the phase balance and the partitioning of nitrogen into the austenite. The partitioning coefficient of nitrogen (the ratio of the mole fraction of nitrogen in the austenite to that in the ferrite) was found to be as high as 7.0 around 1300 K. Consequently, the volume fraction of austenite was influenced by relatively small additions of nitrogen. The results are compared with the experimentally observed data in a duplex stainless steel weld metal in conjunction with the solid state δ → δ + γ phase transformation. Particular attention was given to the morphological instability of grain boundary austenite allotriomorphs. A compariso between the experimental results and calculations indicated that the instability associated with irregular austenite perturbations results from the high degree of undercooling. The results suggest that the model can be used successfully to understand the development of the microstructure in duplex stainless steel weld metals.

Annealing and temperature coefficient study of type IA fibre Bragg gratings inscribed under strain and no strain - Implications to optical fibre component reliability

The annealing properties of Type IA Bragg gratings are investigated and compared with Type I and Type IIA Bragg gratings. The transmission properties (mean and modulated wavelength components) of gratings held at predetermined temperatures are recorded from which decay characteristics are inferred. Our data show critical results concerning the high temperature stability of Type IA gratings, as they undergo a drastic initial decay at 100°C, with a consequent mean index change that is severely reduced at this temperature However, the modulated index change of IA gratings remains stable at lower annealing temperatures of 80°C, and the mean index change decays at a comparable rate to Type I gratings at 80°C. Extending this work to include the thermal decay of Type IA gratings inscribed under strain shows that the application of strain quite dramatically transforms the temperature characteristics of the Type IA grating, modifying the temperature coefficient and annealing curves, with the grating showing a remarkable improvement in high temperature stability, leading to a robust grating that can survive temperatures exceeding 180°C. Under conditions of inscription under strain it is found that the temperature coefficient increases, but is maintained at a value considerably different to the Type I grating. Therefore, the combination of Type I and IA (strained) gratings make it possible to decouple temperature and strain over larger temperature excursions.

A Partition Metric for Clustering Features Analysis

A new distance function to compare arbitrary partitions is proposed. Clustering of image collections and image segmentation give objects to be matched. Offered metric intends for combination of visual features and metadata analysis to solve a semantic gap between low-level visual features and high-level human concept.

New negative temperature coefficient thermistor ceramics in Mn-doped CaCu3-xMnxTi4O12 (0≤x≤1) system

New negative temperature coefficient (NTC) ceramics based on CaCu 3-xMnxTi4O12 (0≤x≤1) compositions have been investigated. The grain size of the CaCu 3-xMnxTi4O12 samples decreases at first and then increases with increasing Mn content. The X-ray photoelectron spectroscopy analysis corroborates the presence of Mn3+ and Mn 4+ in Mn-doped samples, which results in a decrease in the activation energy. All the NTC thermistors prepared show a linear relationship between the natural logarithm of the resistivity and the reciprocal temperature, indicative of NTC characteristics. The Mn-doped CaCu3-xMnxTi 4O12 NTC thermistors provide various electrical properties, depending on Mn content. The values of ρ25, B constant and activation energy of the NTC thermistors are in the range of 2.22×106-3.22×108 Ω cm, 5488-8031 K, and 0.473-0.692 eV, respectively. © 2014 Elsevier Ltd and Techna Group S.r.l. All rights reserved.

Estimation of productivity in Korean electric power plants:a semiparametric smooth coefficient model

This paper analyzes the impact of load factor, facility and generator types on the productivity of Korean electric power plants. In order to capture important differences in the effect of load policy on power output, we use a semiparametric smooth coefficient (SPSC) model that allows us to model heterogeneous performances across power plants and over time by allowing underlying technologies to be heterogeneous. The SPSC model accommodates both continuous and discrete covariates. Various specification tests are conducted to assess the performance of the SPSC model. Using a unique generator level panel dataset spanning the period 1995-2006, we find that the impact of load factor, generator and facility types on power generation varies substantially in terms of magnitude and significance across different plant characteristics. The results have strong implications for generation policy in Korea as outlined in this study.

Modelling stock volatilities during financial crises:a time varying coefficient approach

We examine how the most prevalent stochastic properties of key financial time series have been affected during the recent financial crises. In particular we focus on changes associated with the remarkable economic events of the last two decades in the volatility dynamics, including the underlying volatility persistence and volatility spillover structure. Using daily data from several key stock market indices, the results of our bivariate GARCH models show the existence of time varying correlations as well as time varying shock and volatility spillovers between the returns of FTSE and DAX, and those of NIKKEI and Hang Seng, which became more prominent during the recent financial crisis. Our theoretical considerations on the time varying model which provides the platform upon which we integrate our multifaceted empirical approaches are also of independent interest. In particular, we provide the general solution for time varying asymmetric GARCH specifications, which is a long standing research topic. This enables us to characterize these models by deriving, first, their multistep ahead predictors, second, the first two time varying unconditional moments, and third, their covariance structure.

Coefficient Estimates for Analytic Functions Concerned with Hankel Determinant

MSC 2010: 30C45

Large Distinct Part Sizes in a Random Integer Partition

A partition of a positive integer n is a way of writing it as the sum of positive integers without regard to order; the summands are called parts. The number of partitions of n, usually denoted by p(n), is determined asymptotically by the famous partition formula of Hardy and Ramanujan [5]. We shall introduce the uniform probability measure P on the set of all partitions of n assuming that the probability 1/p(n) is assigned to each n-partition. The symbols E and V ar will be further used to denote the expectation and variance with respect to the measure P . Thus, each conceivable numerical characteristic of the parts in a partition can be regarded as a random variable.

The Number of Parts of Given Multiplicity in a Random Integer Partition

2000 Mathematics Subject Classification: 05A16, 05A17.

Analysing Conjoint Analysis Data by a Random Coefficient Regression Model

2000 Mathematics Subject Classification: 62J12, 62K15, 91B42, 62H99.