Unsupervised random forest: a tutorial with case studies

Unsupervised methods, such as principal component analysis, have gained popularity and wide‐spread acceptance in the chemometrics and applied statistics communities. Unsupervised random forest is an additional method capable of discovering underlying patterns in the data. However, the number of applications of unsupervised random forest in chemometrics has been limited. One possible cause for this is the belief that random forest can only be used in a supervised analysis setting. This tutorial introduces the basic concepts of unsupervised random forest and illustrates several applications in chemometrics through worked examples. Copyright © 2016 John Wiley & Sons, Ltd.     

一个多元校正的稳健诊断新方法

提出一种新的稳健诊断方法，与最小二乘估计结合进行混合物光谱中非线性点的诊断。文中探讨了该方法的性能，用计算机数字模拟及实际多组分光谱体系夺其进行检验，展示了此诊断方法在分析化学计量学中实际应用的可行性。     

化学计量学中的稳健估计方法

稳健统计学是八十年未才基本定型的统计学分支，它是针对实际情况中假设模型常常只是对实际数据的一种近似而导致传统统计学推断失误而发展起来的。稳健统计学构造一些新的具有稳健性的方法，使得在假设模型满足时，稳健方法具有接近最优的性能；在实际数据与假设模型有差别时，其性能仍为次优的；而在实际数据与假设模型差别大时，统计方法的性能也不会变得过差。本文介绍了稳健估计的一般概念。综述了化学计量学中的稳健估计方法，     

分析化学计量学中的新方法─—小波分析

小波分析在分析信号处理中具有诸多显著的优点。本文介绍了小波分析的一般描述，综述了化学计量学在的小波新方法，并展望了小波分析在分析化学计量学中的应用前景。     

最小一乘稳健多元分析校正

本文论述最小一乘求解的多元分析校正算法，探讨了最小一乘较常规最小二乘法及其他隐健算法的优点。用计算机数值模拟及实际多组分光谱体系对方法进行了检验，展示了最小一乘法在分析化学计量学中实际应用的可行性。     

MATLAB在化学计量学中的应用

化学计量学是数学和统计学，化学及计算机科学相互交叉形成的一门新的化学分支学科，是解决化学问题的强有力工具，目前运用于化学计量学的商品软件有MATLAB、Maple,MathCAD,EXCEL,SPSS等。MATLAB是一种高性能的数值计算的科学计算语言，具有程序开发环境简洁直观，数值稳定性好，函数资源丰富的特点，本文以几种常用的化学计量学方法为例，讨论了MATLAB在化学中的应用。     

化学计量学在稀土分析中的应用及进展

本文对化学计量学在吸光光度法、荧光光度法、ICP- AES等稀土分析中的应用进行评述 ,并指出了化学计量学在稀土分析应用中的发展方向 .引用参考文献 98篇     

A short history of chemometrics: a personal view

This article traces chemometrics back to its origins in scientific computing in the 1960s. Its development is compared in other computational disciplines such as bioinformatics. The change in geographical origins of papers published in the core chemometrics literature is discussed. It is concluded that the level of core activities in this area has hardly changed over several decades, whilst there has been a significant expansion in non‐expert users of packages over this period. It is estimated that around 2% of people encountering chemometrics in their research can be considered real experts. The problems of non‐experts using chemometrics methods with limited knowledge of the statistical fundamentals are explored. The contrasting development of chemometrics compared with, for example, computational chemistry and bioinformatics, is interpreted in terms of the changing financial pressures on research over its key developmental phase, as illustrated by the change in academic finance in the UK over the past 50 years. Copyright © 2014 John Wiley & Sons, Ltd.     

信息论与化学计量学

本文讨论了信息论在发展分析化学计量学中的意义和作用以及信息论在化学计量学中应用的一般规律和关系，总结了信息科学对化学计量学发展的贡献。     

Molecular challenges in modern chemometrics

Since the very beginning of the discipline, chemometrics has mainly focussed on analytical chemical problems such as calibration. With the growing importance of databases and applications in medicinal and computational chemistry, the domains of analytical chemistry and chemometrics have been enlarged significantly in recent years. Especially the relation between molecular structure and function has become of considerable interest. Despite the huge quantities of data that are available nowadays, it is often difficult to recognise and extract relevant chemical information for the problem at hand. One of the main obstacles is the definition of an appropriate representation of a molecule. Although a variety of different representations are used, none are generally applicable.

This paper focuses on the challenges that arise in the chemometrical analysis of molecular structures, the relation between structure and function and the relation between molecular representation and chemometrical modelling. Exciting opportunities for further research are illustrated using an example concerning the prediction of co-crystallisation behaviour for small organic molecules with cephalosporin antibiotics.     

Does chemometrics enhance the performance of electroanalysis?

This review explores the question whether chemometrics methods enhance the performance of electroanalytical methods. Electroanalysis has long benefited from the well-established techniques such as potentiometric titrations, polarography and voltammetry, and the more novel ones such as electronic tongues and noses, which have enlarged the scope of applications. The electroanalytical methods have been improved with the application of chemometrics for simultaneous quantitative prediction of analytes or qualitative resolution of complex overlapping responses. Typical methods include partial least squares (PLS), artificial neural networks (ANNs), and multiple curve resolution methods (MCR-ALS, N-PLS and PARAFAC). This review aims to provide the practising analyst with a broad guide to electroanalytical applications supported by chemometrics. In this context, after a general consideration of the use of a number of electroanalytical techniques with the aid of chemometrics methods, several overviews follow with each one focusing on an important field of application such as food, pharmaceuticals, pesticides and the environment. The growth of chemometrics in conjunction with electronic tongue and nose sensors is highlighted, and this is followed by an overview of the use of chemometrics for the resolution of complicated profiles for qualitative identification of analytes, especially with the use of the MCR-ALS methodology. Finally, the performance of electroanalytical methods is compared with that of some spectrophotometric procedures on the basis of figures-of-merit. This showed that electroanalytical methods can perform as well as the spectrophotometric ones. PLS-1 appears to be the method of practical choice if the %relative prediction error of ∼±10% is acceptable.     

Meeting reports: International conference on chemometrics in analytical chemistry

In the field of analytical chemistry, chemometrics has been defined as 'the chemical discipline which uses mathematical and statistical methods to achieve the aim of analytical chemistry, namely the obtention, in the optimal way, of relevant information about material systems'. There has been a tremendous growth of interest in the role of chemometrics in analytical chemistry in recent years and this has been reflected in the number of symposia devoted to the subject. Two meetings, held in Europe in September 1982, covered different aspects of chemometrics and some of the more significant points discussed are summarized in the reports below.     

分析化学计量学

本文是《分析试验室》第五篇“分析化学计量学”专题定期评述文章。评述了１９９７年１月至１９９８年１２月我国分析化学计量学的主要进展。内容涉及统计学与统计方法、试验设计与优化、分析信号处理、多元校正、化学模式识别、定量构效关系（ＱＳＡＲ）、数据库及专家系统、化学计量学教学等方面,共引用文献１６８篇。     

含未知干扰物体系的多元光度分析的化学计量学算法

基于投影矩阵算法和最小熵概念,本文提出了处理含部份未知成份体系的定性定量分析新方法。将此法应用于金属离子及多环芳烃混合物体系测定,获得了满意的结果。     

化学计量学在锕系元素分析中的应用

锕系元素的化学性质相似,各元素的分离和分析都很困难,用传统的数据解析手段,难以实现各元素的同时、快速分析。化学计量学是一种高效、功能强大的数据解析方法,对于样品复杂,基体干扰严重以及多组分样品的分析具有独特优势。将化学计量学应用于锕系元素的分析中,利用数学分离代替化学分离,可直接对样品进行测定。化学计量学方法也可用来指导试样的科学采集,进行实验设计、仪器分析操作条件选择等。从吸收光谱、ICP–AES及放射性测量3个方面综述了化学计量学在锕系元素分析中的应用,阐明了化学计量学在锕系元素分析中的应用难点及发展前景。     

化学计量学在海洛因来源判别中的应用

介绍化学计量学在非法海洛因来源判别中的意义和需求,并结合国际上关于非法海洛因来源判别的应用现状和技术特点讲述了化学计量方法的应用种类和特点。虽然各国所采用的化学计量学方法各异,但基本上可以划分为表观判别法和数理统计法两大类。     

近红外光谱技术用于花生油中棕榈油含量的测定

本文采用近红外光谱技术采集样品的近红外光谱数据,光谱经一阶求导后,采用偏最小二乘法(PLS)建立花生油中棕榈油含量的定标模型,并用交互验证法对模型进行了验证。模型相关系数为0.9963,校正均方根(RMSEC)为0.937。该模型应用于实际样品的检测,结果令人满意。     

Classification and Prediction of Geological Samples by Principal Component Analysis

The principal component analysis is an ancient multivariate statistical method[1]. It is extensively used in spectrometry with the popularization of computer and development of the method of chemometrics. It is regarded as an effective method of multivariate statistical analysis. The principal component analysis is universally included in common program package of multivariate statistical analysis. The method, as well as other multivariate calibration methods, combined with artificial neural networks forms the foundation of the chemometrics.     

Development of an HPLC Assay Methodology for a Desonide Cream with Chemometrics Assisted Optimization

A new reversed-phase liquid chromatographic method for the separation and simultaneous quantification of desonide, sorbic acid, methylparaben, propyl gallate, and the major degradation product of desonide in a hydrophilic cream was developed with the aid of experimental design, resolution loss functions, and chemometrics methods. A strategy involving a screening phase and a fractional factorial design revealed the most influent chromatographic variables (pH and organic solvent content). The arc tangent resolution function was adopted as the optimization loss function. These variables were further optimized using a central composite design. Multivariate curve resolution and partial least squares regression were tested to optimize the chromatographic run time. The latter revealed to be superior in terms of precision and allowed the validation of a method with a total run time 3 times lower (approximately 8 min). The experimental design and chemometrics models enabled an efficient use of time and resources in predicting the optimum separation conditions for the desonide formulation. The validation of the resulting method according to the current ICH guidelines confirmed its selectivity, linearity, accuracy, and precision.     

化学计量学在速差动力学分析中的应用及进展

化学计量学在动力学多组分分析中的应用是近年来非常活跃的领域。本文从多元校正、卡尔曼滤波、协同效应校正、人工神经网络及计算机应用等方面对化学计量学速差动力学分析领域出现的新方法及新动向作一评述,并对今后的工作进行了展望。引用文献99篇。