The emphasis is on new or recent methods in industrial Chemistry.

Focus of the special issue is on following 4 topics:

(1) Principles of modelling by PLS. Properties of PLS regression. Comparison with other regression methods, especially Ridge Regression. Validation of PLS Regression.

(2) Use of weights in modelling data. PLS can be viewed as weights on variables. It can be extended to include weights on samples. Use of weights on samples in Classification procedures. Simultaneous regression analysis and classification. Double regression on score and loading vectors of X. Relationships between X and other data matrices. Tasks involving projections onto score and loading vectors. Two-way analysis of X. Extension of two-way analysis to multi-way analysis of data.

(3) Forecasting and control at industrial processes. Multiple, simultaneous forecasting of processes. Multiple forecast methods, where forecasts are used in further forecasts. Finding paths among processes, where multiple forecasting can be carried out. Administration of interconnected processes. Supervision and control of sub-processes by forecasting methods. Possibility of establishing Control Centers to evaluate the performance of processes, and make decisions on the ongoing production at earliest possible stage of the production.

(4) Analysis of production data at industrial chemical companies. Use of overall and historical data. Establish relationships between variables. Quality variables during production. Relationships between quality/environmental variables with process/production/content variables and determination of, when they can be estimated. Latent variation in production data. Detection of trend, special ‘movement’ of data, groups in data. Warning systems for ‘out-of-control’ of variables. Influence of raw materials or starting variables on production.

We welcome researchers from various disciplines to provide interdisciplinary perspectives on the issue's themes.