Suppose we have a factorial experiment with m factors where the ith factor has Si levels, i = 1, 2,…, m. The v = mIIi=1 Si level combinations laid out in a v × b block design D with block sizes k1, k2,…, kb and replications ri,r2,…, rv. The C-matrix for the design is given by C = rδ−Nk−δN1 (1) where rδ =diag(r1,r2,…,rv) k−δ=diag(k−11, k−11,….,k−1b) Nv×b = incidence matrix of the design. The reduced normal equations are given by Ct = Q (2) Q is the vector of adjusted treatment total where t1 = {…t(x1,x2,…,xm)…} (3) is the vector of treatment effects arranged lexicographically, t(x1,x2,…., xm) being the treatment effect at the level combination x = (x1, x2,…., xm) x1 = 0, 1, …, Si -1, i = 1(1)m. We know that for δi = 0 or 1 ∀i, such that δ = (δi, δ2,…, δm) ≠ (0 0…0), an interaction Fδ1,1… Fδ2,2 … Fδmm contains (s1 − 1)δ1 (s2 − 1)δ2… (sm − 1)δm = f(δ) orthonormal contrasts among the v treatment effect t(x) which are given by (4)(P δ1 1 ⊗ P δ2 2 ⊗ P δm m )t=F δ Where (5) P δi i = 1 s i (1, 1, …, 1) 1 × s i if δ = 0 = P (s i −1)×s i if δ i = 1 such that 1 s i (1, 1, …, 1) P i is a δi × δi orthogonal matrix and ⊗ denotes Kronecker product of matrices. Fδ = Fδ11 Fδ22 … Fδmm is said to balanced if either Fδ is not estimable or if (6) dispersion (P δ 1 1 ⊗ … ⊗ P δ m m ) t = σ 2 I f(σ) .λ(δ) when Fδ is estimable, where If(δ) is the identity matrix of order f(δ),λ(δ) is a positive constant depending on 6 and t is any solution of (1.2). If from a design all the factorial effects are balanced, then the design is said to be balanced. If the BLUE's of the treatment contrasts belonging to different factorial effects {Fδ}, are uncorrelated then we say that the design has orthogonal factorial structure (OFS). It is known that a connected, proper, equireplicate and binary design is balanced and has OFS if and only if the design is an Extended Group Divisible design. Pioneering works in this direction can be found in Nair and Rao (1948), Shah (1958, 1960), Kurkjian and Zelen (1963), Kshirsagar (1966) and Hinkelmann and Kempthrone (1963)). A comprehensive study in this respect can be found in Gupta and Mukerjee (1989). Now, some efforts have been made to generalise this concept, where the contrasts belonging to a particular effect are classified in some way and designs have been proposed which allow orthogonal estimation with balance, of the effect contrasts belonging to different classes of the effects. Such designs may be called partially balanced factorial designs. One such design was studied in Das and Chatterjee (1999), where the contrasts belonging to factorial effects were classified by introducing groups among the levels of the factors. In the prime-power symmetric case, there is a standard pencilwise division of the factorial effects (Bose and Kishen 1940, Bose 1947). We have considered this division of factorial effects here and characterised designs allowing orthogonal estimation with balance of the treatment contrasts belonging to different pencils. We have called such designs as pencilwise orthogonal and balanced (FOB) designs. We have observed that a design is FOB if and only if its C-matrix is a particular type of linear combination of the Kronecker products of circulant permutation matrices. In particular, a binary, proper and equireplicate design is FOB if and only if it is a PBIB design based on a ( s m − 1) ( s − 1) associate class PBIB association scheme which we have called ‘pencilwise association (PA) scheme’. The association scheme as well as the designs deserve special attention because the designs available so far (Bose and Kishen 1940, Bose 1947) are resolvable designs where the set of blocks forming a replicate forms a disconnected GD design with block size as power of s. Such designs are obtained by cyclical developments of one or more initial blocks. These designs form a sub-class of FOB designs, which need not be resolvable, nor juxtaposition of disconnected GD designs with block sizes as power of s in general.
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